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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 10x RNA-seq gene expression data\n",
+    "\n",
+    "To efficiently handle data transfer and download, the 4 million cell 10X dataset, was subdivide into 24 expression matrices where cells are grouped by 10X chemistry (10Xv2, 10Xv3 and 10XMulti) and the broad anatomical region from where the cells were dissected from.\n",
+    "\n",
+    "The purpose of this set of notebooks is to provide an overview of the data, the file organization and how to combine data and metadata through example use cases. This notebook introduces you to TileDB (and TileDB-Soma) and the efficient data read and complex queries. Along the way, you will learn about the use of the 10x data in the Allen Brain Atlas through comparison of annodata and tiledb.\n",
+    "\n",
+    "You need to be connected to the internet to run this notebook and that you have downloaded the example data via the getting started notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Import the necessary libraries\n",
+    "import os\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import anndata\n",
+    "import time\n",
+    "import matplotlib.pyplot as plt\n",
+    "import json\n",
+    "import requests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "  tiledbsoma version: 1.2.2\n",
+      "  tiledb-py version:  0.21.3\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Import the tiledb libraries\n",
+    "import tiledb\n",
+    "import tiledbsoma as soma\n",
+    "import tiledbsoma.io\n",
+    "# enable logging\n",
+    "tiledbsoma.logging.info()\n",
+    "vfs = tiledb.VFS()\n",
+    "\n",
+    "# check version\n",
+    "print(\n",
+    "    f\"\"\"\n",
+    "  tiledbsoma version: {soma.__version__}\n",
+    "  tiledb-py version:  {tiledb.__version__}\n",
+    "\"\"\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The prerequisite for running this notebook is that the data have been downloaded to local directory maintaining the organization from the manifest.json. **Change the download_base variable to where you have downloaded the data in your system.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "version = '20230830'\n",
+    "download_base = '/shared/Data/abc_download_root' # You can replace this with your own download root\n",
+    "\n",
+    "use_local_cache = False\n",
+    "manifest_path = 'releases/%s/manifest.json' % version\n",
+    "\n",
+    "if not use_local_cache :\n",
+    "    url = 'https://allen-brain-cell-atlas.s3-us-west-2.amazonaws.com/' + manifest_path\n",
+    "    manifest = json.loads(requests.get(url).text)\n",
+    "else :\n",
+    "    file = os.path.join(download_base,manifest_path)\n",
+    "    with open(file,'rb') as f:\n",
+    "        manifest = json.load(f)\n",
+    "    \n",
+    "metadata = manifest['file_listing']['WMB-10X']['metadata']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "view_directory = os.path.join( download_base, \n",
+    "                               manifest['directory_listing']['WMB-10X']['directories']['metadata']['relative_path'], \n",
+    "                              'views')\n",
+    "cache_views = False\n",
+    "if cache_views :\n",
+    "    os.makedirs( view_directory, exist_ok=True )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data overview\n",
+    "### Cell metadata\n",
+    "\n",
+    "Essential cell metadata is stored as a dataframe. Each row represents one cell indexed by a *cell label*. The *cell label* is the concatenation of barcode and name of the sample. In this context, the sample is the *barcoded cell sample* that represents a single load into one port of the 10x Chromium. Note that cell barcodes are only unique within a single *barcoded cell sample* and that the same barcode can be reused. The *barcoded cell sample* label or name is unique in the database.\n",
+    "\n",
+    "Each cell is associated with a *library label*, *library method*, *donor label*, *donor genotype*, *donor sex*, dissection *region of interest acronym\", the corresponding coarse *anatomical division label* and the *matrix_prefix* identifying which data package this cell is part of.\n",
+    "\n",
+    "Further, each cell is associated with a *cluster alias* representing which cluster this cell is a member of and (x,y) coordinates of the all cells UMAP in Figure 1 of the manuscript.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file: /shared/Data/abc_download_root/metadata/WMB-10X/20230830/cell_metadata.csv\n",
+      "Number of cells =  4042976\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>barcoded_cell_sample_label</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>feature_matrix_label</th>\n",
+       "      <th>entity</th>\n",
+       "      <th>brain_section_label</th>\n",
+       "      <th>library_method</th>\n",
+       "      <th>region_of_interest_acronym</th>\n",
+       "      <th>donor_label</th>\n",
+       "      <th>donor_genotype</th>\n",
+       "      <th>donor_sex</th>\n",
+       "      <th>dataset_label</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "      <th>cluster_alias</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cell_label</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>GCGAGAAGTTAAGGGC-410_B05</th>\n",
+       "      <td>GCGAGAAGTTAAGGGC</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>F</td>\n",
+       "      <td>WMB-10Xv3</td>\n",
+       "      <td>23.146826</td>\n",
+       "      <td>-3.086639</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AATGGCTCAGCTCCTT-411_B06</th>\n",
+       "      <td>AATGGCTCAGCTCCTT</td>\n",
+       "      <td>411_B06</td>\n",
+       "      <td>L8TX_201029_01_E10</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550851</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>F</td>\n",
+       "      <td>WMB-10Xv3</td>\n",
+       "      <td>23.138481</td>\n",
+       "      <td>-3.022000</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AACACACGTTGCTTGA-410_B05</th>\n",
+       "      <td>AACACACGTTGCTTGA</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>F</td>\n",
+       "      <td>WMB-10Xv3</td>\n",
+       "      <td>23.472557</td>\n",
+       "      <td>-2.992709</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CACAGATAGAGGCGGA-410_A05</th>\n",
+       "      <td>CACAGATAGAGGCGGA</td>\n",
+       "      <td>410_A05</td>\n",
+       "      <td>L8TX_201029_01_A10</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>F</td>\n",
+       "      <td>WMB-10Xv3</td>\n",
+       "      <td>23.379622</td>\n",
+       "      <td>-3.043442</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AAAGTGAAGCATTTCG-410_B05</th>\n",
+       "      <td>AAAGTGAAGCATTTCG</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>F</td>\n",
+       "      <td>WMB-10Xv3</td>\n",
+       "      <td>23.909480</td>\n",
+       "      <td>-2.601536</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              cell_barcode barcoded_cell_sample_label   \n",
+       "cell_label                                                              \n",
+       "GCGAGAAGTTAAGGGC-410_B05  GCGAGAAGTTAAGGGC                    410_B05  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  AATGGCTCAGCTCCTT                    411_B06   \n",
+       "AACACACGTTGCTTGA-410_B05  AACACACGTTGCTTGA                    410_B05   \n",
+       "CACAGATAGAGGCGGA-410_A05  CACAGATAGAGGCGGA                    410_A05   \n",
+       "AAAGTGAAGCATTTCG-410_B05  AAAGTGAAGCATTTCG                    410_B05   \n",
+       "\n",
+       "                               library_label feature_matrix_label entity   \n",
+       "cell_label                                                                 \n",
+       "GCGAGAAGTTAAGGGC-410_B05  L8TX_201030_01_C12        WMB-10Xv3-HPF   cell  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  L8TX_201029_01_E10        WMB-10Xv3-HPF   cell   \n",
+       "AACACACGTTGCTTGA-410_B05  L8TX_201030_01_C12        WMB-10Xv3-HPF   cell   \n",
+       "CACAGATAGAGGCGGA-410_A05  L8TX_201029_01_A10        WMB-10Xv3-HPF   cell   \n",
+       "AAAGTGAAGCATTTCG-410_B05  L8TX_201030_01_C12        WMB-10Xv3-HPF   cell   \n",
+       "\n",
+       "                          brain_section_label library_method   \n",
+       "cell_label                                                     \n",
+       "GCGAGAAGTTAAGGGC-410_B05                  NaN          10Xv3  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06                  NaN          10Xv3   \n",
+       "AACACACGTTGCTTGA-410_B05                  NaN          10Xv3   \n",
+       "CACAGATAGAGGCGGA-410_A05                  NaN          10Xv3   \n",
+       "AAAGTGAAGCATTTCG-410_B05                  NaN          10Xv3   \n",
+       "\n",
+       "                         region_of_interest_acronym   \n",
+       "cell_label                                            \n",
+       "GCGAGAAGTTAAGGGC-410_B05                        RHP  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06                        RHP   \n",
+       "AACACACGTTGCTTGA-410_B05                        RHP   \n",
+       "CACAGATAGAGGCGGA-410_A05                        RHP   \n",
+       "AAAGTGAAGCATTTCG-410_B05                        RHP   \n",
+       "\n",
+       "                                           donor_label    donor_genotype   \n",
+       "cell_label                                                                 \n",
+       "GCGAGAAGTTAAGGGC-410_B05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  Snap25-IRES2-Cre;Ai14-550851  Ai14(RCL-tdT)/wt   \n",
+       "AACACACGTTGCTTGA-410_B05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt   \n",
+       "CACAGATAGAGGCGGA-410_A05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt   \n",
+       "AAAGTGAAGCATTTCG-410_B05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt   \n",
+       "\n",
+       "                         donor_sex dataset_label          x         y   \n",
+       "cell_label                                                              \n",
+       "GCGAGAAGTTAAGGGC-410_B05         F     WMB-10Xv3  23.146826 -3.086639  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06         F     WMB-10Xv3  23.138481 -3.022000   \n",
+       "AACACACGTTGCTTGA-410_B05         F     WMB-10Xv3  23.472557 -2.992709   \n",
+       "CACAGATAGAGGCGGA-410_A05         F     WMB-10Xv3  23.379622 -3.043442   \n",
+       "AAAGTGAAGCATTTCG-410_B05         F     WMB-10Xv3  23.909480 -2.601536   \n",
+       "\n",
+       "                          cluster_alias  \n",
+       "cell_label                               \n",
+       "GCGAGAAGTTAAGGGC-410_B05              1  \n",
+       "AATGGCTCAGCTCCTT-411_B06              1  \n",
+       "AACACACGTTGCTTGA-410_B05              1  \n",
+       "CACAGATAGAGGCGGA-410_A05              1  \n",
+       "AAAGTGAAGCATTTCG-410_B05              1  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rpath = metadata['cell_metadata']['files']['csv']['relative_path']\n",
+    "file = os.path.join( download_base, rpath)\n",
+    "print(f\"Reading file: {file}\")\n",
+    "cell = pd.read_csv(file, dtype={'cell_label':str})\n",
+    "cell.set_index('cell_label',inplace=True)\n",
+    "print(\"Number of cells = \", len(cell))\n",
+    "cell.head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can use panadas groupby function to see how many unique items are associated for each field and list them out if the number of items is small."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def print_column_info(df) :\n",
+    "    \n",
+    "    for c in df.columns :\n",
+    "        grouped = df[[c]].groupby(c).count()\n",
+    "        members = ''\n",
+    "        if len(grouped) < 30 :\n",
+    "            members = str(list(grouped.index))\n",
+    "        print(\"Number of unique %s = %d %s\" % (c,len(grouped),members))        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of unique cell_barcode = 2375490 \n",
+      "Number of unique barcoded_cell_sample_label = 819 \n",
+      "Number of unique library_label = 819 \n",
+      "Number of unique feature_matrix_label = 24 ['WMB-10XMulti', 'WMB-10Xv2-CTXsp', 'WMB-10Xv2-HPF', 'WMB-10Xv2-HY', 'WMB-10Xv2-Isocortex-1', 'WMB-10Xv2-Isocortex-2', 'WMB-10Xv2-Isocortex-3', 'WMB-10Xv2-Isocortex-4', 'WMB-10Xv2-MB', 'WMB-10Xv2-OLF', 'WMB-10Xv2-TH', 'WMB-10Xv3-CB', 'WMB-10Xv3-CTXsp', 'WMB-10Xv3-HPF', 'WMB-10Xv3-HY', 'WMB-10Xv3-Isocortex-1', 'WMB-10Xv3-Isocortex-2', 'WMB-10Xv3-MB', 'WMB-10Xv3-MY', 'WMB-10Xv3-OLF', 'WMB-10Xv3-P', 'WMB-10Xv3-PAL', 'WMB-10Xv3-STR', 'WMB-10Xv3-TH']\n",
+      "Number of unique entity = 1 ['cell']\n",
+      "Number of unique brain_section_label = 0 []\n",
+      "Number of unique library_method = 3 ['10Xv2', '10Xv3', '10xRSeq_Mult']\n",
+      "Number of unique region_of_interest_acronym = 29 ['ACA', 'AI', 'AUD', 'AUD-TEa-PERI-ECT', 'CB', 'CTXsp', 'ENT', 'HIP', 'HY', 'LSX', 'MB', 'MO-FRP', 'MOp', 'MY', 'OLF', 'P', 'PAL', 'PL-ILA-ORB', 'RHP', 'RSP', 'SS-GU-VISC', 'SSp', 'STRd', 'STRv', 'TEa-PERI-ECT', 'TH', 'VIS', 'VIS-PTLp', 'sAMY']\n",
+      "Number of unique donor_label = 345 \n",
+      "Number of unique donor_genotype = 5 ['Ai14(RCL-tdT)/wt', 'Gad2-IRES-Cre/wt;Ai14(RCL-tdT)/wt', 'Slc32a1-IRES-Cre/wt;Ai14(RCL-tdT)/wt', 'Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt', 'wt/wt']\n",
+      "Number of unique donor_sex = 2 ['F', 'M']\n",
+      "Number of unique dataset_label = 3 ['WMB-10XMulti', 'WMB-10Xv2', 'WMB-10Xv3']\n",
+      "Number of unique x = 3992539 \n",
+      "Number of unique y = 3992791 \n",
+      "Number of unique cluster_alias = 5322 \n"
+     ]
+    }
+   ],
+   "source": [
+    "print_column_info(cell)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>x</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dataset_label</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>WMB-10XMulti</th>\n",
+       "      <td>1687</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>WMB-10Xv2</th>\n",
+       "      <td>1699939</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>WMB-10Xv3</th>\n",
+       "      <td>2341350</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     x\n",
+       "dataset_label         \n",
+       "WMB-10XMulti      1687\n",
+       "WMB-10Xv2      1699939\n",
+       "WMB-10Xv3      2341350"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.groupby('dataset_label')[['x']].count()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also bring in the pivot table from the \"cluster annotation tutorial\" to associate each cell with terms at each cell type classification level."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "taxonomy_metadata = manifest['file_listing']['WMB-taxonomy']['metadata']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file: /shared/Data/abc_download_root/metadata/WMB-taxonomy/20230830/views/cluster_to_cluster_annotation_membership_pivoted.csv\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>neurotransmitter</th>\n",
+       "      <th>class</th>\n",
+       "      <th>subclass</th>\n",
+       "      <th>supertype</th>\n",
+       "      <th>cluster</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cluster_alias</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Glut</td>\n",
+       "      <td>01 IT-ET Glut</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Glut</td>\n",
+       "      <td>01 IT-ET Glut</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0327 L2 IT PPP-APr Glut_3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Glut</td>\n",
+       "      <td>01 IT-ET Glut</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0081 L2 IT PPP-APr Glut_2</td>\n",
+       "      <td>0322 L2 IT PPP-APr Glut_2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Glut</td>\n",
+       "      <td>01 IT-ET Glut</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0081 L2 IT PPP-APr Glut_2</td>\n",
+       "      <td>0323 L2 IT PPP-APr Glut_2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Glut</td>\n",
+       "      <td>01 IT-ET Glut</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0081 L2 IT PPP-APr Glut_2</td>\n",
+       "      <td>0325 L2 IT PPP-APr Glut_2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              neurotransmitter          class                subclass   \n",
+       "cluster_alias                                                           \n",
+       "1                         Glut  01 IT-ET Glut  018 L2 IT PPP-APr Glut  \\\n",
+       "2                         Glut  01 IT-ET Glut  018 L2 IT PPP-APr Glut   \n",
+       "3                         Glut  01 IT-ET Glut  018 L2 IT PPP-APr Glut   \n",
+       "4                         Glut  01 IT-ET Glut  018 L2 IT PPP-APr Glut   \n",
+       "5                         Glut  01 IT-ET Glut  018 L2 IT PPP-APr Glut   \n",
+       "\n",
+       "                               supertype                    cluster  \n",
+       "cluster_alias                                                        \n",
+       "1              0082 L2 IT PPP-APr Glut_3  0326 L2 IT PPP-APr Glut_3  \n",
+       "2              0082 L2 IT PPP-APr Glut_3  0327 L2 IT PPP-APr Glut_3  \n",
+       "3              0081 L2 IT PPP-APr Glut_2  0322 L2 IT PPP-APr Glut_2  \n",
+       "4              0081 L2 IT PPP-APr Glut_2  0323 L2 IT PPP-APr Glut_2  \n",
+       "5              0081 L2 IT PPP-APr Glut_2  0325 L2 IT PPP-APr Glut_2  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rpath = taxonomy_metadata['cluster_to_cluster_annotation_membership_pivoted']['files']['csv']['relative_path']\n",
+    "file = os.path.join( download_base, rpath)\n",
+    "print(f\"Reading file: {file}\")\n",
+    "cluster_details = pd.read_csv(file,keep_default_na=False)\n",
+    "cluster_details.set_index('cluster_alias', inplace=True)\n",
+    "cluster_details.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file: /shared/Data/abc_download_root/metadata/WMB-taxonomy/20230830/views/cluster_to_cluster_annotation_membership_color.csv\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>neurotransmitter_color</th>\n",
+       "      <th>class_color</th>\n",
+       "      <th>subclass_color</th>\n",
+       "      <th>supertype_color</th>\n",
+       "      <th>cluster_color</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cluster_alias</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#CCA73D</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#002BCC</td>\n",
+       "      <td>#99000D</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#002BCC</td>\n",
+       "      <td>#5C8899</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#002BCC</td>\n",
+       "      <td>#473D66</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              neurotransmitter_color class_color subclass_color   \n",
+       "cluster_alias                                                     \n",
+       "1                            #2B93DF     #FA0087        #0F6632  \\\n",
+       "2                            #2B93DF     #FA0087        #0F6632   \n",
+       "3                            #2B93DF     #FA0087        #0F6632   \n",
+       "4                            #2B93DF     #FA0087        #0F6632   \n",
+       "5                            #2B93DF     #FA0087        #0F6632   \n",
+       "\n",
+       "              supertype_color cluster_color  \n",
+       "cluster_alias                                \n",
+       "1                     #266DFF       #64661F  \n",
+       "2                     #266DFF       #CCA73D  \n",
+       "3                     #002BCC       #99000D  \n",
+       "4                     #002BCC       #5C8899  \n",
+       "5                     #002BCC       #473D66  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rpath = taxonomy_metadata['cluster_to_cluster_annotation_membership_color']['files']['csv']['relative_path']\n",
+    "file = os.path.join( download_base, rpath)\n",
+    "print(f\"Reading file: {file}\")\n",
+    "cluster_colors = pd.read_csv(file)\n",
+    "cluster_colors.set_index('cluster_alias', inplace=True)\n",
+    "cluster_colors.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file: /shared/Data/abc_download_root/metadata/WMB-10X/20230830/region_of_interest_metadata.csv\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>label</th>\n",
+       "      <th>name</th>\n",
+       "      <th>region_of_interest_order</th>\n",
+       "      <th>region_of_interest_color</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>acronym</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>MO-FRP</th>\n",
+       "      <td>WMB-MO-FRP</td>\n",
+       "      <td>Somatomotor - Frontal pole</td>\n",
+       "      <td>0</td>\n",
+       "      <td>#3DCC7C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MOp</th>\n",
+       "      <td>WMB-MOp</td>\n",
+       "      <td>Primary motor area</td>\n",
+       "      <td>1</td>\n",
+       "      <td>#179968</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SS-GU-VISC</th>\n",
+       "      <td>WMB-SS-GU-VISC</td>\n",
+       "      <td>Somatosensory/gustatory/visceral areas</td>\n",
+       "      <td>2</td>\n",
+       "      <td>#2E8599</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SSp</th>\n",
+       "      <td>WMB-SSp</td>\n",
+       "      <td>Primary somatosensory area</td>\n",
+       "      <td>3</td>\n",
+       "      <td>#5CCCCC</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AUD</th>\n",
+       "      <td>WMB-AUD</td>\n",
+       "      <td>Auditory areas</td>\n",
+       "      <td>4</td>\n",
+       "      <td>#455A99</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     label                                    name   \n",
+       "acronym                                                              \n",
+       "MO-FRP          WMB-MO-FRP              Somatomotor - Frontal pole  \\\n",
+       "MOp                WMB-MOp                      Primary motor area   \n",
+       "SS-GU-VISC  WMB-SS-GU-VISC  Somatosensory/gustatory/visceral areas   \n",
+       "SSp                WMB-SSp              Primary somatosensory area   \n",
+       "AUD                WMB-AUD                          Auditory areas   \n",
+       "\n",
+       "            region_of_interest_order region_of_interest_color  \n",
+       "acronym                                                        \n",
+       "MO-FRP                             0                  #3DCC7C  \n",
+       "MOp                                1                  #179968  \n",
+       "SS-GU-VISC                         2                  #2E8599  \n",
+       "SSp                                3                  #5CCCCC  \n",
+       "AUD                                4                  #455A99  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rpath = metadata['region_of_interest_metadata']['files']['csv']['relative_path']\n",
+    "file = os.path.join( download_base, rpath)\n",
+    "print(f\"Reading file: {file}\")\n",
+    "roi = pd.read_csv(file)\n",
+    "roi.set_index('acronym',inplace=True)\n",
+    "roi.rename(columns={'order':'region_of_interest_order','color_hex_triplet':'region_of_interest_color'},inplace=True)\n",
+    "roi.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>barcoded_cell_sample_label</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>feature_matrix_label</th>\n",
+       "      <th>entity</th>\n",
+       "      <th>brain_section_label</th>\n",
+       "      <th>library_method</th>\n",
+       "      <th>region_of_interest_acronym</th>\n",
+       "      <th>donor_label</th>\n",
+       "      <th>donor_genotype</th>\n",
+       "      <th>...</th>\n",
+       "      <th>subclass</th>\n",
+       "      <th>supertype</th>\n",
+       "      <th>cluster</th>\n",
+       "      <th>neurotransmitter_color</th>\n",
+       "      <th>class_color</th>\n",
+       "      <th>subclass_color</th>\n",
+       "      <th>supertype_color</th>\n",
+       "      <th>cluster_color</th>\n",
+       "      <th>region_of_interest_order</th>\n",
+       "      <th>region_of_interest_color</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cell_label</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>GCGAGAAGTTAAGGGC-410_B05</th>\n",
+       "      <td>GCGAGAAGTTAAGGGC</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AATGGCTCAGCTCCTT-411_B06</th>\n",
+       "      <td>AATGGCTCAGCTCCTT</td>\n",
+       "      <td>411_B06</td>\n",
+       "      <td>L8TX_201029_01_E10</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550851</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AACACACGTTGCTTGA-410_B05</th>\n",
+       "      <td>AACACACGTTGCTTGA</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CACAGATAGAGGCGGA-410_A05</th>\n",
+       "      <td>CACAGATAGAGGCGGA</td>\n",
+       "      <td>410_A05</td>\n",
+       "      <td>L8TX_201029_01_A10</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AAAGTGAAGCATTTCG-410_B05</th>\n",
+       "      <td>AAAGTGAAGCATTTCG</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 27 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              cell_barcode barcoded_cell_sample_label   \n",
+       "cell_label                                                              \n",
+       "GCGAGAAGTTAAGGGC-410_B05  GCGAGAAGTTAAGGGC                    410_B05  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  AATGGCTCAGCTCCTT                    411_B06   \n",
+       "AACACACGTTGCTTGA-410_B05  AACACACGTTGCTTGA                    410_B05   \n",
+       "CACAGATAGAGGCGGA-410_A05  CACAGATAGAGGCGGA                    410_A05   \n",
+       "AAAGTGAAGCATTTCG-410_B05  AAAGTGAAGCATTTCG                    410_B05   \n",
+       "\n",
+       "                               library_label feature_matrix_label entity   \n",
+       "cell_label                                                                 \n",
+       "GCGAGAAGTTAAGGGC-410_B05  L8TX_201030_01_C12        WMB-10Xv3-HPF   cell  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  L8TX_201029_01_E10        WMB-10Xv3-HPF   cell   \n",
+       "AACACACGTTGCTTGA-410_B05  L8TX_201030_01_C12        WMB-10Xv3-HPF   cell   \n",
+       "CACAGATAGAGGCGGA-410_A05  L8TX_201029_01_A10        WMB-10Xv3-HPF   cell   \n",
+       "AAAGTGAAGCATTTCG-410_B05  L8TX_201030_01_C12        WMB-10Xv3-HPF   cell   \n",
+       "\n",
+       "                          brain_section_label library_method   \n",
+       "cell_label                                                     \n",
+       "GCGAGAAGTTAAGGGC-410_B05                  NaN          10Xv3  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06                  NaN          10Xv3   \n",
+       "AACACACGTTGCTTGA-410_B05                  NaN          10Xv3   \n",
+       "CACAGATAGAGGCGGA-410_A05                  NaN          10Xv3   \n",
+       "AAAGTGAAGCATTTCG-410_B05                  NaN          10Xv3   \n",
+       "\n",
+       "                         region_of_interest_acronym   \n",
+       "cell_label                                            \n",
+       "GCGAGAAGTTAAGGGC-410_B05                        RHP  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06                        RHP   \n",
+       "AACACACGTTGCTTGA-410_B05                        RHP   \n",
+       "CACAGATAGAGGCGGA-410_A05                        RHP   \n",
+       "AAAGTGAAGCATTTCG-410_B05                        RHP   \n",
+       "\n",
+       "                                           donor_label    donor_genotype  ...   \n",
+       "cell_label                                                                ...   \n",
+       "GCGAGAAGTTAAGGGC-410_B05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt  ...  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  Snap25-IRES2-Cre;Ai14-550851  Ai14(RCL-tdT)/wt  ...   \n",
+       "AACACACGTTGCTTGA-410_B05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt  ...   \n",
+       "CACAGATAGAGGCGGA-410_A05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt  ...   \n",
+       "AAAGTGAAGCATTTCG-410_B05  Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt  ...   \n",
+       "\n",
+       "                                        subclass                  supertype   \n",
+       "cell_label                                                                    \n",
+       "GCGAGAAGTTAAGGGC-410_B05  018 L2 IT PPP-APr Glut  0082 L2 IT PPP-APr Glut_3  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  018 L2 IT PPP-APr Glut  0082 L2 IT PPP-APr Glut_3   \n",
+       "AACACACGTTGCTTGA-410_B05  018 L2 IT PPP-APr Glut  0082 L2 IT PPP-APr Glut_3   \n",
+       "CACAGATAGAGGCGGA-410_A05  018 L2 IT PPP-APr Glut  0082 L2 IT PPP-APr Glut_3   \n",
+       "AAAGTGAAGCATTTCG-410_B05  018 L2 IT PPP-APr Glut  0082 L2 IT PPP-APr Glut_3   \n",
+       "\n",
+       "                                            cluster  neurotransmitter_color   \n",
+       "cell_label                                                                    \n",
+       "GCGAGAAGTTAAGGGC-410_B05  0326 L2 IT PPP-APr Glut_3                 #2B93DF  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06  0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "AACACACGTTGCTTGA-410_B05  0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "CACAGATAGAGGCGGA-410_A05  0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "AAAGTGAAGCATTTCG-410_B05  0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "\n",
+       "                          class_color subclass_color supertype_color   \n",
+       "cell_label                                                             \n",
+       "GCGAGAAGTTAAGGGC-410_B05      #FA0087        #0F6632         #266DFF  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06      #FA0087        #0F6632         #266DFF   \n",
+       "AACACACGTTGCTTGA-410_B05      #FA0087        #0F6632         #266DFF   \n",
+       "CACAGATAGAGGCGGA-410_A05      #FA0087        #0F6632         #266DFF   \n",
+       "AAAGTGAAGCATTTCG-410_B05      #FA0087        #0F6632         #266DFF   \n",
+       "\n",
+       "                         cluster_color region_of_interest_order   \n",
+       "cell_label                                                        \n",
+       "GCGAGAAGTTAAGGGC-410_B05       #64661F                       15  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06       #64661F                       15   \n",
+       "AACACACGTTGCTTGA-410_B05       #64661F                       15   \n",
+       "CACAGATAGAGGCGGA-410_A05       #64661F                       15   \n",
+       "AAAGTGAAGCATTTCG-410_B05       #64661F                       15   \n",
+       "\n",
+       "                         region_of_interest_color  \n",
+       "cell_label                                         \n",
+       "GCGAGAAGTTAAGGGC-410_B05                  #CCB05C  \n",
+       "AATGGCTCAGCTCCTT-411_B06                  #CCB05C  \n",
+       "AACACACGTTGCTTGA-410_B05                  #CCB05C  \n",
+       "CACAGATAGAGGCGGA-410_A05                  #CCB05C  \n",
+       "AAAGTGAAGCATTTCG-410_B05                  #CCB05C  \n",
+       "\n",
+       "[5 rows x 27 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell_extended = cell.join(cluster_details,on='cluster_alias')\n",
+    "cell_extended = cell_extended.join(cluster_colors,on='cluster_alias')\n",
+    "cell_extended = cell_extended.join(roi[['region_of_interest_order','region_of_interest_color']],on='region_of_interest_acronym')\n",
+    "cell_extended.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of unique cell_barcode = 2375490 \n",
+      "Number of unique barcoded_cell_sample_label = 819 \n",
+      "Number of unique library_label = 819 \n",
+      "Number of unique feature_matrix_label = 24 ['WMB-10XMulti', 'WMB-10Xv2-CTXsp', 'WMB-10Xv2-HPF', 'WMB-10Xv2-HY', 'WMB-10Xv2-Isocortex-1', 'WMB-10Xv2-Isocortex-2', 'WMB-10Xv2-Isocortex-3', 'WMB-10Xv2-Isocortex-4', 'WMB-10Xv2-MB', 'WMB-10Xv2-OLF', 'WMB-10Xv2-TH', 'WMB-10Xv3-CB', 'WMB-10Xv3-CTXsp', 'WMB-10Xv3-HPF', 'WMB-10Xv3-HY', 'WMB-10Xv3-Isocortex-1', 'WMB-10Xv3-Isocortex-2', 'WMB-10Xv3-MB', 'WMB-10Xv3-MY', 'WMB-10Xv3-OLF', 'WMB-10Xv3-P', 'WMB-10Xv3-PAL', 'WMB-10Xv3-STR', 'WMB-10Xv3-TH']\n",
+      "Number of unique entity = 1 ['cell']\n",
+      "Number of unique brain_section_label = 0 []\n",
+      "Number of unique library_method = 3 ['10Xv2', '10Xv3', '10xRSeq_Mult']\n",
+      "Number of unique region_of_interest_acronym = 29 ['ACA', 'AI', 'AUD', 'AUD-TEa-PERI-ECT', 'CB', 'CTXsp', 'ENT', 'HIP', 'HY', 'LSX', 'MB', 'MO-FRP', 'MOp', 'MY', 'OLF', 'P', 'PAL', 'PL-ILA-ORB', 'RHP', 'RSP', 'SS-GU-VISC', 'SSp', 'STRd', 'STRv', 'TEa-PERI-ECT', 'TH', 'VIS', 'VIS-PTLp', 'sAMY']\n",
+      "Number of unique donor_label = 345 \n",
+      "Number of unique donor_genotype = 5 ['Ai14(RCL-tdT)/wt', 'Gad2-IRES-Cre/wt;Ai14(RCL-tdT)/wt', 'Slc32a1-IRES-Cre/wt;Ai14(RCL-tdT)/wt', 'Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt', 'wt/wt']\n",
+      "Number of unique donor_sex = 2 ['F', 'M']\n",
+      "Number of unique dataset_label = 3 ['WMB-10XMulti', 'WMB-10Xv2', 'WMB-10Xv3']\n",
+      "Number of unique x = 3992539 \n",
+      "Number of unique y = 3992791 \n",
+      "Number of unique cluster_alias = 5322 \n",
+      "Number of unique neurotransmitter = 10 ['', 'Chol', 'Dopa', 'GABA', 'GABA-Glyc', 'Glut', 'Glut-GABA', 'Hist', 'Nora', 'Sero']\n",
+      "Number of unique class = 34 \n",
+      "Number of unique subclass = 338 \n",
+      "Number of unique supertype = 1201 \n",
+      "Number of unique cluster = 5322 \n",
+      "Number of unique neurotransmitter_color = 10 ['#03EDFF', '#0a9964', '#2B93DF', '#533691', '#666666', '#73E785', '#820e57', '#FF3358', '#fcf04b', '#ff7621']\n",
+      "Number of unique class_color = 34 \n",
+      "Number of unique subclass_color = 338 \n",
+      "Number of unique supertype_color = 1201 \n",
+      "Number of unique cluster_color = 5298 \n",
+      "Number of unique region_of_interest_order = 29 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]\n",
+      "Number of unique region_of_interest_color = 29 ['#0059CC', '#00990A', '#00FFCF', '#179968', '#26AEFF', '#2E8599', '#300099', '#341FCC', '#34CC1F', '#3DCC7C', '#455A99', '#4D58FF', '#5CCCCC', '#6F9945', '#84FF4D', '#8CCC00', '#992E6A', '#994817', '#99922E', '#9F3DCC', '#B973FF', '#CC0026', '#CC5CB0', '#CCB05C', '#E4FF26', '#FF00EF', '#FF2678', '#FF7373', '#FF8F00']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print_column_info(cell_extended)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For convenience, we can cache this view for later reuse. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "if cache_views :\n",
+    "    file = os.path.join( view_directory, 'cell_metadata_with_cluster_annotation.csv')\n",
+    "    cell_extended.to_csv( file )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### UMAP spatial embedding\n",
+    "\n",
+    "Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualizing and exploring large-dimension datasets. The x, y columns of the cell metadata table represents the coordinate of the all cells UMAP in Figure 1 of the manuscript. \n",
+    "\n",
+    "We define a small helper function *plot umap* to visualize the cells on the UMAP colorized by: dissection region of interest, neurotransmitter identity, cell types division, class and subclass. For ease of demostration, we do a simple subsampling of the cells by a factor of 10 to reduce processing time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def plot_umap( xx, yy, cc=None, val=None, fig_width = 8, fig_height = 8, cmap=None ) :\n",
+    "    \n",
+    "    fig, ax = plt.subplots()\n",
+    "    fig.set_size_inches(fig_width, fig_height)\n",
+    "    \n",
+    "    if cmap is not None :\n",
+    "        plt.scatter(xx,yy,s=0.5,c=val,marker='.',cmap=cmap)\n",
+    "    elif cc is not None :\n",
+    "        plt.scatter(xx,yy,s=0.5,color=cc,marker='.')\n",
+    "        \n",
+    "    ax.axis('equal')\n",
+    "    ax.set_xlim(-18,27)\n",
+    "    ax.set_ylim(-18,27)\n",
+    "    ax.set_xticks([])\n",
+    "    ax.set_yticks([])\n",
+    "    \n",
+    "    return fig, ax"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "404298\n"
+     ]
+    }
+   ],
+   "source": [
+    "cell_subsampled = cell_extended.loc[::10]\n",
+    "print(len(cell_subsampled))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_umap( cell_subsampled['x'], cell_subsampled['y'], cc=cell_subsampled['region_of_interest_color'])\n",
+    "res = ax.set_title(\"Dissection Region Of Interest\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_umap( cell_subsampled['x'], cell_subsampled['y'], cc=cell_subsampled['neurotransmitter_color'])\n",
+    "res = ax.set_title(\"Neuortransmitter Identity\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_umap( cell_subsampled['x'], cell_subsampled['y'], cc=cell_subsampled['class_color'])\n",
+    "res = ax.set_title(\"Cell Types: Class\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plot_umap( cell_subsampled['x'], cell_subsampled['y'], cc=cell_subsampled['subclass_color'])\n",
+    "res = ax.set_title(\"Cell Types: Subclass\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Single cell transcriptomes\n",
+    "\n",
+    "Each 10x library was sequenced on the Illumina NovaSeq6000 platform, and sequencing reads were aligned to the mouse \n",
+    "reference transcriptome mm10 (GENCODE vM23/Ensembl 98) using the 10x Genomics CellRanger pipeline (version 6.1.1) with default parameters. Each gene is uniquely identifier by an Ensembl ID. It is best practice to gene identifier to for tracking and data interchange as gene symbols are not unique and can change over time\n",
+    "\n",
+    "Each row of the gene dataframe has Ensembl gene identifier, a gene symbol and name. 1173 genes have no expression across all the cells in the dataset and can be identified by \"no expression\" in the comment column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file: /shared/Data/abc_download_root/metadata/WMB-10X/20230830/gene.csv\n",
+      "Number of genes =  32285\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene_symbol</th>\n",
+       "      <th>name</th>\n",
+       "      <th>mapped_ncbi_identifier</th>\n",
+       "      <th>comment</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000051951</th>\n",
+       "      <td>Xkr4</td>\n",
+       "      <td>X-linked Kx blood group related 4</td>\n",
+       "      <td>NCBIGene:497097</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000089699</th>\n",
+       "      <td>Gm1992</td>\n",
+       "      <td>predicted gene 1992</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000102331</th>\n",
+       "      <td>Gm19938</td>\n",
+       "      <td>predicted gene, 19938</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000102343</th>\n",
+       "      <td>Gm37381</td>\n",
+       "      <td>predicted gene, 37381</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000025900</th>\n",
+       "      <td>Rp1</td>\n",
+       "      <td>retinitis pigmentosa 1 (human)</td>\n",
+       "      <td>NCBIGene:19888</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   gene_symbol                               name   \n",
+       "gene_identifier                                                     \n",
+       "ENSMUSG00000051951        Xkr4  X-linked Kx blood group related 4  \\\n",
+       "ENSMUSG00000089699      Gm1992                predicted gene 1992   \n",
+       "ENSMUSG00000102331     Gm19938              predicted gene, 19938   \n",
+       "ENSMUSG00000102343     Gm37381              predicted gene, 37381   \n",
+       "ENSMUSG00000025900         Rp1     retinitis pigmentosa 1 (human)   \n",
+       "\n",
+       "                   mapped_ncbi_identifier comment  \n",
+       "gene_identifier                                    \n",
+       "ENSMUSG00000051951        NCBIGene:497097     NaN  \n",
+       "ENSMUSG00000089699                    NaN     NaN  \n",
+       "ENSMUSG00000102331                    NaN     NaN  \n",
+       "ENSMUSG00000102343                    NaN     NaN  \n",
+       "ENSMUSG00000025900         NCBIGene:19888     NaN  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rpath = metadata['gene']['files']['csv']['relative_path']\n",
+    "file = os.path.join( download_base, rpath)\n",
+    "print(f\"Reading file: {file}\")\n",
+    "gene = pd.read_csv(file)\n",
+    "gene.set_index('gene_identifier',inplace=True)\n",
+    "print(\"Number of genes = \", len(gene))\n",
+    "gene.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of no expression genes 1173\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene_symbol</th>\n",
+       "      <th>name</th>\n",
+       "      <th>mapped_ncbi_identifier</th>\n",
+       "      <th>comment</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000118272</th>\n",
+       "      <td>Arhgef4</td>\n",
+       "      <td>Rho guanine nucleotide exchange factor (GEF) 4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000117809</th>\n",
+       "      <td>Asdurf</td>\n",
+       "      <td>Asnsd1 upstream reading frame</td>\n",
+       "      <td>NCBIGene:110599589</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000047383</th>\n",
+       "      <td>AC169382.1</td>\n",
+       "      <td>novel transcript</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000097001</th>\n",
+       "      <td>1700054K02Rik</td>\n",
+       "      <td>RIKEN cDNA 1700054K02 gene</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000116048</th>\n",
+       "      <td>Sept2</td>\n",
+       "      <td>septin 2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000091585</th>\n",
+       "      <td>AC140365.1</td>\n",
+       "      <td>PRAME family member 8-like</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000095523</th>\n",
+       "      <td>AC124606.1</td>\n",
+       "      <td>PRAME family member 8-like</td>\n",
+       "      <td>NCBIGene:100038995</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000095475</th>\n",
+       "      <td>AC133095.2</td>\n",
+       "      <td>uncharacterized LOC545763</td>\n",
+       "      <td>NCBIGene:545763</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000094855</th>\n",
+       "      <td>AC133095.1</td>\n",
+       "      <td>uncharacterized LOC620639</td>\n",
+       "      <td>NCBIGene:620639</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000095019</th>\n",
+       "      <td>AC234645.1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>no expression</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1173 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      gene_symbol   \n",
+       "gene_identifier                     \n",
+       "ENSMUSG00000118272        Arhgef4  \\\n",
+       "ENSMUSG00000117809         Asdurf   \n",
+       "ENSMUSG00000047383     AC169382.1   \n",
+       "ENSMUSG00000097001  1700054K02Rik   \n",
+       "ENSMUSG00000116048          Sept2   \n",
+       "...                           ...   \n",
+       "ENSMUSG00000091585     AC140365.1   \n",
+       "ENSMUSG00000095523     AC124606.1   \n",
+       "ENSMUSG00000095475     AC133095.2   \n",
+       "ENSMUSG00000094855     AC133095.1   \n",
+       "ENSMUSG00000095019     AC234645.1   \n",
+       "\n",
+       "                                                              name   \n",
+       "gene_identifier                                                      \n",
+       "ENSMUSG00000118272  Rho guanine nucleotide exchange factor (GEF) 4  \\\n",
+       "ENSMUSG00000117809                   Asnsd1 upstream reading frame   \n",
+       "ENSMUSG00000047383                                novel transcript   \n",
+       "ENSMUSG00000097001                      RIKEN cDNA 1700054K02 gene   \n",
+       "ENSMUSG00000116048                                        septin 2   \n",
+       "...                                                            ...   \n",
+       "ENSMUSG00000091585                      PRAME family member 8-like   \n",
+       "ENSMUSG00000095523                      PRAME family member 8-like   \n",
+       "ENSMUSG00000095475                       uncharacterized LOC545763   \n",
+       "ENSMUSG00000094855                       uncharacterized LOC620639   \n",
+       "ENSMUSG00000095019                                             NaN   \n",
+       "\n",
+       "                   mapped_ncbi_identifier        comment  \n",
+       "gene_identifier                                           \n",
+       "ENSMUSG00000118272                    NaN  no expression  \n",
+       "ENSMUSG00000117809     NCBIGene:110599589  no expression  \n",
+       "ENSMUSG00000047383                    NaN  no expression  \n",
+       "ENSMUSG00000097001                    NaN  no expression  \n",
+       "ENSMUSG00000116048                    NaN  no expression  \n",
+       "...                                   ...            ...  \n",
+       "ENSMUSG00000091585                    NaN  no expression  \n",
+       "ENSMUSG00000095523     NCBIGene:100038995  no expression  \n",
+       "ENSMUSG00000095475        NCBIGene:545763  no expression  \n",
+       "ENSMUSG00000094855        NCBIGene:620639  no expression  \n",
+       "ENSMUSG00000095019                    NaN  no expression  \n",
+       "\n",
+       "[1173 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pred = (gene['comment']=='no expression')\n",
+    "filtered = gene[pred]\n",
+    "print(\"Number of no expression genes\", len(filtered))\n",
+    "filtered"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Gene expression matrices"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The 4 million cell dataset has been divided into 24 expression matrices to make data transfer and download more efficient. Each package is formatted as an annadata h5ad file with minimal metadata. In this next section, we provide example code on how to open one of the expression matrix files and connect with the rich cell level metadata discussed above.\n",
+    "\n",
+    "For each subset, there are two h5ad files one storing the raw counts and the other log normalization of it. For this example, we will use the log2 version of the expression matrix."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "expression_matrices = manifest['file_listing']['WMB-10Xv2']['expression_matrices']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'log2': {'files': {'h5ad': {'version': '20230630',\n",
+       "    'relative_path': 'expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad',\n",
+       "    'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad',\n",
+       "    'size': 4038679930}}},\n",
+       " 'raw': {'files': {'h5ad': {'version': '20230630',\n",
+       "    'relative_path': 'expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad',\n",
+       "    'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad',\n",
+       "    'size': 4038679930}}}}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "feature_matrix_label = 'WMB-10Xv2-TH'\n",
+    "expression_matrices[feature_matrix_label]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n"
+     ]
+    }
+   ],
+   "source": [
+    "rpath = expression_matrices[feature_matrix_label]['log2']['files']['h5ad']['relative_path']\n",
+    "file = os.path.join( download_base, rpath)\n",
+    "print(file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "For ease of operation, the equivalent tiledb soma conversion file is located in the same directory level as the WMB-10Xv2 expression matrix files. \n",
+    "\n",
+    "Note that each TileDB conversion file is composed of arrays stored on HHD in a ``directory``."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get the relative path to the WMB-10Xv2-TH-log2 expression matrix file.\n",
+    "log2_expression_matrix_file_path = expression_matrices[feature_matrix_label]['log2']['files']['h5ad']['relative_path']\n",
+    "\n",
+    "# Construct the path to the tiledb soma conversion directory.\n",
+    "tiledb_soma_conversion_directory = os.path.join(download_base, 'expression_matrices', 'WMB-10Xv2-TDB', '20230630')\n",
+    "\n",
+    "# Construct the path to the tiledb soma conversion file.\n",
+    "tiledb_soma_conversion_folder_path = os.path.join(tiledb_soma_conversion_directory, feature_matrix_label + '-log2')\n",
+    "\n",
+    "# Print the path to the tiledb soma conversion file.\n",
+    "print(tiledb_soma_conversion_folder_path)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We use the anndata's *read_h5ad* function to open the package for the log2 normalization file. The \"backed='r'\" makes use of the lazy loading functionality to only load required data. By default, anndata will load the entire expression matrix in memory."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AnnData object with n_obs × n_vars = 131212 × 32285 backed at '/shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad'\n",
+      "    obs: 'cell_barcode', 'library_label', 'anatomical_division_label'\n",
+      "    var: 'gene_symbol'\n",
+      "    uns: 'normalization', 'parent', 'parent_layer', 'parent_rows'\n"
+     ]
+    }
+   ],
+   "source": [
+    "adata = anndata.read_h5ad(file,backed='r')\n",
+    "print(adata)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Reading TileDB SOMA\n",
+    "SOMA TileDB is a storage format that allows working with large files without having to fully load them in memory. Files can be either read from disk or from a remote source, like an S3 bucket.\n",
+    "\n",
+    "The core feature of SOMA is to allow reading subsets of the data using slices: only the portion of required data is read from disk/network. SOMA uses Apache Arrow as an intermediate in-memory storage. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setting up the uri\n",
+    "To open the tiledb soma conversion file, you need to specify the tiledb soma uri (Accessor for the object's storage URI).\n",
+    "You can read more about the tiledb soma uri here: https://tiledbsoma.readthedocs.io/en/latest/_autosummary/tiledbsoma.Experiment.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# open\n",
+    "tdbs = tiledbsoma.Experiment.open(tiledb_soma_conversion_folder_path) # uri in this case is \"tiledb_soma_conversion_folder_path\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "6.144e-06"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# We can use TileDB's VFS to inspect the final size of the SOMA\n",
+    "vfs.file_size(tiledb_soma_conversion_folder_path) / 1e9"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.06012577"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vfs.dir_size(tiledb_soma_conversion_folder_path) / 1e9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An Experiment is a class that represents a single-cell experiment. It always contains two objects: 1. obs: A DataFrame with primary annotations on the observation axis. 2. ms: A Collection of measurements.\n",
+    "You can learn more about the Experiment class here: https://tiledbsoma.readthedocs.io/en/latest/_autosummary/tiledbsoma.Experiment.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<Experiment '/shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2' (open for 'r') (2 items)\n",
+      "    'ms': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms' (unopened)\n",
+      "    'obs': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/obs' (unopened)>\n"
+     ]
+    }
+   ],
+   "source": [
+    "# check obs and ms of tdbs experiment\n",
+    "print(tdbs) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once the data has been ingested into a TileDB SOMA it's stored in an analysis-ready format that can be sliced directly without having to load the entire dataset into memory. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "A SOMA can be sliced by *cell/feature* identifiers or by filtering on the cell/feature annotations stored in the `obs`/`var` arrays. For example, we can slice all expression data across only the `cell_type` of *platelet*. TileDB intelligently uses its indexes in order to fetch only the relevant portions of the object that satisfy the query, hence achieving rapid query performance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 74.9 ms, sys: 31.6 ms, total: 107 ms\n",
+      "Wall time: 205 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[131212, 32285]"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "[tdbs.obs.count, tdbs.ms[\"RNA\"].var.count]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can access the SOMA `DataFrame` containing the cell-level annotations using the `.obs` property."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/obs' (open for 'r')>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# check obs\n",
+    "tdbs.obs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "('soma_joinid',\n",
+       " 'cell_label',\n",
+       " 'cell_barcode',\n",
+       " 'library_label',\n",
+       " 'anatomical_division_label')"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tdbs.obs.keys()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All read operations need to be performed using the `.read()` method. By default, `.read()` returns a Python iterator and each iteration returns a [PyArrow Table](https://arrow.apache.org/docs/python/generated/pyarrow.Table.html). However, we can call the `.concat()` and `.to_pandas()` methods to automatically concate the results and return a single [Pandas DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>cell_label</th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>anatomical_division_label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA-040_C01</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA</td>\n",
+       "      <td>L8TX_180815_01_E08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC-045_C01</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC</td>\n",
+       "      <td>L8TX_180829_01_C10</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>CGATGTATCTTGCCGT-042_B01</td>\n",
+       "      <td>CGATGTATCTTGCCGT</td>\n",
+       "      <td>L8TX_180829_01_B09</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>GACTAACGTCCTCTTG-040_B01</td>\n",
+       "      <td>GACTAACGTCCTCTTG</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GATCGTACAACTGCTA-040_B01</td>\n",
+       "      <td>GATCGTACAACTGCTA</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131207</th>\n",
+       "      <td>131207</td>\n",
+       "      <td>GTACTCCGTAGTACCT-103_B01</td>\n",
+       "      <td>GTACTCCGTAGTACCT</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131208</th>\n",
+       "      <td>131208</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC-103_B01</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131209</th>\n",
+       "      <td>131209</td>\n",
+       "      <td>ACACCCTCATGCGCAC-103_C01</td>\n",
+       "      <td>ACACCCTCATGCGCAC</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131210</th>\n",
+       "      <td>131210</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT-103_C01</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131211</th>\n",
+       "      <td>131211</td>\n",
+       "      <td>TCTGGAAAGATGAGAG-103_C01</td>\n",
+       "      <td>TCTGGAAAGATGAGAG</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>131212 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        soma_joinid                cell_label      cell_barcode   \n",
+       "0                 0  CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA  \\\n",
+       "1                 1  TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC   \n",
+       "2                 2  CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT   \n",
+       "3                 3  GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG   \n",
+       "4                 4  GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA   \n",
+       "...             ...                       ...               ...   \n",
+       "131207       131207  GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT   \n",
+       "131208       131208  GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC   \n",
+       "131209       131209  ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC   \n",
+       "131210       131210  CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT   \n",
+       "131211       131211  TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG   \n",
+       "\n",
+       "             library_label anatomical_division_label  \n",
+       "0       L8TX_180815_01_E08                        TH  \n",
+       "1       L8TX_180829_01_C10                        TH  \n",
+       "2       L8TX_180829_01_B09                        TH  \n",
+       "3       L8TX_180815_01_D08                        TH  \n",
+       "4       L8TX_180815_01_D08                        TH  \n",
+       "...                    ...                       ...  \n",
+       "131207  L8TX_190321_01_G03                        TH  \n",
+       "131208  L8TX_190321_01_G03                        TH  \n",
+       "131209  L8TX_190321_01_H03                        TH  \n",
+       "131210  L8TX_190321_01_H03                        TH  \n",
+       "131211  L8TX_190321_01_H03                        TH  \n",
+       "\n",
+       "[131212 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# read obs as pandas dataframe\n",
+    "tdbs.obs.read().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Collection 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms' (open for 'r') (1 item)\n",
+       "    'RNA': Measurement 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA' (open for 'r') (3 items)\n",
+       "        'X': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X' (unopened)\n",
+       "        'var': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')\n",
+       "        'uns': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/uns' (unopened)>"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# check ms\n",
+    "tdbs.ms"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Access the SOMA `Measurement` containing the raw RNA counts data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Measurement 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA' (open for 'r') (3 items)\n",
+       "    'X': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X' (unopened)\n",
+       "    'var': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')\n",
+       "    'uns': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/uns' (unopened)>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Access SOMA measurement containing raw counts data\n",
+    "tdbs.ms[\"RNA\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Read the feature-level annotations from the `Measurement` as a Pandas DataFrame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>ENSMUSG00000051951</td>\n",
+       "      <td>Xkr4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>ENSMUSG00000089699</td>\n",
+       "      <td>Gm1992</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>ENSMUSG00000102331</td>\n",
+       "      <td>Gm19938</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>ENSMUSG00000102343</td>\n",
+       "      <td>Gm37381</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>ENSMUSG00000025900</td>\n",
+       "      <td>Rp1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32280</th>\n",
+       "      <td>32280</td>\n",
+       "      <td>ENSMUSG00000095523</td>\n",
+       "      <td>AC124606.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32281</th>\n",
+       "      <td>32281</td>\n",
+       "      <td>ENSMUSG00000095475</td>\n",
+       "      <td>AC133095.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32282</th>\n",
+       "      <td>32282</td>\n",
+       "      <td>ENSMUSG00000094855</td>\n",
+       "      <td>AC133095.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32283</th>\n",
+       "      <td>32283</td>\n",
+       "      <td>ENSMUSG00000095019</td>\n",
+       "      <td>AC234645.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32284</th>\n",
+       "      <td>32284</td>\n",
+       "      <td>ENSMUSG00000095041</td>\n",
+       "      <td>AC149090.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>32285 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       soma_joinid     gene_identifier gene_symbol\n",
+       "0                0  ENSMUSG00000051951        Xkr4\n",
+       "1                1  ENSMUSG00000089699      Gm1992\n",
+       "2                2  ENSMUSG00000102331     Gm19938\n",
+       "3                3  ENSMUSG00000102343     Gm37381\n",
+       "4                4  ENSMUSG00000025900         Rp1\n",
+       "...            ...                 ...         ...\n",
+       "32280        32280  ENSMUSG00000095523  AC124606.1\n",
+       "32281        32281  ENSMUSG00000095475  AC133095.2\n",
+       "32282        32282  ENSMUSG00000094855  AC133095.1\n",
+       "32283        32283  ENSMUSG00000095019  AC234645.1\n",
+       "32284        32284  ENSMUSG00000095041  AC149090.1\n",
+       "\n",
+       "[32285 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Read the feature-level annotations from the measurements as a panda dataframe\n",
+    "tdbs.ms[\"RNA\"].var.read().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Read the raw RNA counts data from the `\"data\"` layer of `X`:\n",
+    "This will take a few seconds. The outcome is a ``pyarrow SparseCOOTensor``. \n",
+    "\n",
+    "Note that the X matrix is a sparse matrix. Sparse matrices are more memory efficient than dense matrices.  Note that shape here indicates the capacity of the tensor, rather than the actual size."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pyarrow.SparseCOOTensor>\n",
+       "type: float\n",
+       "shape: (9223372036854773760, 9223372036854773760)"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# read raw RNA counts from the 'data' layer of X\n",
+    "tdbs.ms[\"RNA\"].X[\"data\"].read().coos().concat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<bound method Mapping.values of <Experiment '/shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2' (open for 'r') (2 items)\n",
+       "    'ms': Collection 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms' (open for 'r') (1 item)\n",
+       "        'RNA': Measurement 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA' (open for 'r') (3 items)\n",
+       "            'X': Collection 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X' (open for 'r') (1 item)\n",
+       "                'data': SparseNDArray 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X/data' (open for 'r')\n",
+       "            'var': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')\n",
+       "            'uns': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/uns' (unopened)\n",
+       "    'obs': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/obs' (open for 'r')>>"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tdbs.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "You can read and slice tiledb. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>cell_label</th>\n",
+       "      <th>anatomical_division_label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA-040_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC-045_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>CGATGTATCTTGCCGT-042_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>GACTAACGTCCTCTTG-040_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GATCGTACAACTGCTA-040_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>95</td>\n",
+       "      <td>ACGCCAGGTTCGGCAC-040_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>96</th>\n",
+       "      <td>96</td>\n",
+       "      <td>AGCCTAAGTGGGTATG-103_A01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>97</th>\n",
+       "      <td>97</td>\n",
+       "      <td>AGCAGCCAGGCTCAGA-036_D01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>98</th>\n",
+       "      <td>98</td>\n",
+       "      <td>ATCATGGGTCTCCACT-041_D01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>99</td>\n",
+       "      <td>CGAATGTTCATTGCCC-038_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    soma_joinid                cell_label anatomical_division_label\n",
+       "0             0  CAGGTGCAGGCTAGCA-040_C01                        TH\n",
+       "1             1  TGCGCAGGTTGCGCAC-045_C01                        TH\n",
+       "2             2  CGATGTATCTTGCCGT-042_B01                        TH\n",
+       "3             3  GACTAACGTCCTCTTG-040_B01                        TH\n",
+       "4             4  GATCGTACAACTGCTA-040_B01                        TH\n",
+       "..          ...                       ...                       ...\n",
+       "95           95  ACGCCAGGTTCGGCAC-040_B01                        TH\n",
+       "96           96  AGCCTAAGTGGGTATG-103_A01                        TH\n",
+       "97           97  AGCAGCCAGGCTCAGA-036_D01                        TH\n",
+       "98           98  ATCATGGGTCTCCACT-041_D01                        TH\n",
+       "99           99  CGAATGTTCATTGCCC-038_C01                        TH\n",
+       "\n",
+       "[100 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tdbs.obs.read(\n",
+    "    coords=[slice(0, 99)],\n",
+    "    # value_filter=\"n_genes > 1200\",\n",
+    "    column_names=[\"soma_joinid\", \"cell_label\", \"anatomical_division_label\"],\n",
+    ").concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Genes are represented as \"variables\". For this data, the *var* dataframe is indexed by the Ensembl gene identifier with one metadata column *gene symbol*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of genes =  32285\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Index(['ENSMUSG00000051951', 'ENSMUSG00000089699', 'ENSMUSG00000102331',\n",
+       "       'ENSMUSG00000102343', 'ENSMUSG00000025900'],\n",
+       "      dtype='object', name='gene_identifier')"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(\"Number of genes = \", len(adata.var))\n",
+    "adata.var.index[0:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's try with tiledb soma"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of genes: 32285\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get the number of genes.\n",
+    "num_genes = len(tdbs.ms[\"RNA\"].var.read().concat().to_pandas())\n",
+    "\n",
+    "# Print the number of genes.\n",
+    "print(\"Number of genes:\", num_genes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of genes: 32285\n",
+      "Index(['ENSMUSG00000051951', 'ENSMUSG00000089699', 'ENSMUSG00000102331',\n",
+      "       'ENSMUSG00000102343', 'ENSMUSG00000025900'],\n",
+      "      dtype='object', name='gene_identifier')\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get the gene identifiers of all genes.\n",
+    "gene_identifiers = tdbs.ms[\"RNA\"].var.read().concat().to_pandas()[\"gene_identifier\"]\n",
+    "\n",
+    "# Print the number of genes.\n",
+    "print(\"Number of genes:\", len(gene_identifiers))\n",
+    "\n",
+    "# Print the gene identifiers of the first 5 genes.\n",
+    "print(pd.Index(gene_identifiers[0:5], name=\"gene_identifier\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Cells are represented as \"observations\". For this data, the *obs* dataframe is index by *cell label* with three minimal metadata columns *cell barcode*, *library label* and *anatomical division label*. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of cells =  131212\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Index(['CAGGTGCAGGCTAGCA-040_C01', 'TGCGCAGGTTGCGCAC-045_C01',\n",
+       "       'CGATGTATCTTGCCGT-042_B01', 'GACTAACGTCCTCTTG-040_B01',\n",
+       "       'GATCGTACAACTGCTA-040_B01'],\n",
+       "      dtype='object', name='cell_label')"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(\"Number of cells = \", len(adata.obs))\n",
+    "adata.obs.index[0:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now let's try this with tiledbsoma"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['CAGGTGCAGGCTAGCA-040_C01', 'TGCGCAGGTTGCGCAC-045_C01',\n",
+      "       'CGATGTATCTTGCCGT-042_B01', 'GACTAACGTCCTCTTG-040_B01',\n",
+      "       'GATCGTACAACTGCTA-040_B01'],\n",
+      "      dtype='object', name='cell_label')\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get the cell labels of the first 5 cells.\n",
+    "cell_labels = tdbs.obs.read().concat().to_pandas()[\"cell_label\"].head(5)\n",
+    "\n",
+    "# Print the cell labels of the first 5 cells.\n",
+    "print(pd.Index(cell_labels, name=\"cell_label\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can easily connect the cells in the package to the extended cell metadata with simple pandas filtering."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of cells =  130555\n"
+     ]
+    }
+   ],
+   "source": [
+    "pred = (cell_extended['feature_matrix_label'] == feature_matrix_label)\n",
+    "cell_filtered = cell_extended[pred]\n",
+    "print(\"Number of cells = \", len(cell_filtered))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You have successfully filtered the large cell_extended DataFrame to create a new DataFrame, cell_filtered, which only contains cells that have a feature_matrix_label matching the specific label \"WMB-10Xv2-TH\". The cell_filtered DataFrame contains 130,555 rows, each representing an individual cell with this particular feature matrix label."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>barcoded_cell_sample_label</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>feature_matrix_label</th>\n",
+       "      <th>entity</th>\n",
+       "      <th>brain_section_label</th>\n",
+       "      <th>library_method</th>\n",
+       "      <th>region_of_interest_acronym</th>\n",
+       "      <th>donor_label</th>\n",
+       "      <th>donor_genotype</th>\n",
+       "      <th>...</th>\n",
+       "      <th>subclass</th>\n",
+       "      <th>supertype</th>\n",
+       "      <th>cluster</th>\n",
+       "      <th>neurotransmitter_color</th>\n",
+       "      <th>class_color</th>\n",
+       "      <th>subclass_color</th>\n",
+       "      <th>supertype_color</th>\n",
+       "      <th>cluster_color</th>\n",
+       "      <th>region_of_interest_order</th>\n",
+       "      <th>region_of_interest_color</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cell_label</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>GCGAGAAGTTAAGGGC-410_B05</th>\n",
+       "      <td>GCGAGAAGTTAAGGGC</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AATGGCTCAGCTCCTT-411_B06</th>\n",
+       "      <td>AATGGCTCAGCTCCTT</td>\n",
+       "      <td>411_B06</td>\n",
+       "      <td>L8TX_201029_01_E10</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550851</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AACACACGTTGCTTGA-410_B05</th>\n",
+       "      <td>AACACACGTTGCTTGA</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CACAGATAGAGGCGGA-410_A05</th>\n",
+       "      <td>CACAGATAGAGGCGGA</td>\n",
+       "      <td>410_A05</td>\n",
+       "      <td>L8TX_201029_01_A10</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AAAGTGAAGCATTTCG-410_B05</th>\n",
+       "      <td>AAAGTGAAGCATTTCG</td>\n",
+       "      <td>410_B05</td>\n",
+       "      <td>L8TX_201030_01_C12</td>\n",
+       "      <td>WMB-10Xv3-HPF</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv3</td>\n",
+       "      <td>RHP</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-550850</td>\n",
+       "      <td>Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>018 L2 IT PPP-APr Glut</td>\n",
+       "      <td>0082 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>0326 L2 IT PPP-APr Glut_3</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#FA0087</td>\n",
+       "      <td>#0F6632</td>\n",
+       "      <td>#266DFF</td>\n",
+       "      <td>#64661F</td>\n",
+       "      <td>15</td>\n",
+       "      <td>#CCB05C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTGTGAGCAAACGCGA-1350_C05</th>\n",
+       "      <td>GTGTGAGCAAACGCGA</td>\n",
+       "      <td>1350_C05</td>\n",
+       "      <td>L8XR_220728_01_A05</td>\n",
+       "      <td>WMB-10XMulti</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10xRSeq_Mult</td>\n",
+       "      <td>MB</td>\n",
+       "      <td>C57BL6J-641405</td>\n",
+       "      <td>wt/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>278 NLL Gata3 Gly-Gaba</td>\n",
+       "      <td>1074 NLL Gata3 Gly-Gaba_1</td>\n",
+       "      <td>4804 NLL Gata3 Gly-Gaba_1</td>\n",
+       "      <td>#820e57</td>\n",
+       "      <td>#72195a</td>\n",
+       "      <td>#E57300</td>\n",
+       "      <td>#a4fcb2</td>\n",
+       "      <td>#C7CC7A</td>\n",
+       "      <td>25</td>\n",
+       "      <td>#CC5CB0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TTAGCAATCCCTGTTA-1350_C05</th>\n",
+       "      <td>TTAGCAATCCCTGTTA</td>\n",
+       "      <td>1350_C05</td>\n",
+       "      <td>L8XR_220728_01_A05</td>\n",
+       "      <td>WMB-10XMulti</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10xRSeq_Mult</td>\n",
+       "      <td>MB</td>\n",
+       "      <td>C57BL6J-641405</td>\n",
+       "      <td>wt/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>157 RN Spp1 Glut</td>\n",
+       "      <td>0682 RN Spp1 Glut_1</td>\n",
+       "      <td>2761 RN Spp1 Glut_1</td>\n",
+       "      <td>#2B93DF</td>\n",
+       "      <td>#007200</td>\n",
+       "      <td>#FF514D</td>\n",
+       "      <td>#BA1FCC</td>\n",
+       "      <td>#3DCC44</td>\n",
+       "      <td>25</td>\n",
+       "      <td>#CC5CB0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TTTGGCTGTCGCGCAA-1350_C05</th>\n",
+       "      <td>TTTGGCTGTCGCGCAA</td>\n",
+       "      <td>1350_C05</td>\n",
+       "      <td>L8XR_220728_01_A05</td>\n",
+       "      <td>WMB-10XMulti</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10xRSeq_Mult</td>\n",
+       "      <td>MB</td>\n",
+       "      <td>C57BL6J-641405</td>\n",
+       "      <td>wt/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>278 NLL Gata3 Gly-Gaba</td>\n",
+       "      <td>1076 NLL Gata3 Gly-Gaba_3</td>\n",
+       "      <td>4806 NLL Gata3 Gly-Gaba_3</td>\n",
+       "      <td>#820e57</td>\n",
+       "      <td>#72195a</td>\n",
+       "      <td>#E57300</td>\n",
+       "      <td>#76CC00</td>\n",
+       "      <td>#FF00CA</td>\n",
+       "      <td>25</td>\n",
+       "      <td>#CC5CB0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ATCCACCTCACAGACT-1320_B04</th>\n",
+       "      <td>ATCCACCTCACAGACT</td>\n",
+       "      <td>1320_B04</td>\n",
+       "      <td>L8XR_220630_02_B10</td>\n",
+       "      <td>WMB-10XMulti</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10xRSeq_Mult</td>\n",
+       "      <td>OLF</td>\n",
+       "      <td>C57BL6J-625156</td>\n",
+       "      <td>wt/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>278 NLL Gata3 Gly-Gaba</td>\n",
+       "      <td>1076 NLL Gata3 Gly-Gaba_3</td>\n",
+       "      <td>4806 NLL Gata3 Gly-Gaba_3</td>\n",
+       "      <td>#820e57</td>\n",
+       "      <td>#72195a</td>\n",
+       "      <td>#E57300</td>\n",
+       "      <td>#76CC00</td>\n",
+       "      <td>#FF00CA</td>\n",
+       "      <td>13</td>\n",
+       "      <td>#FF7373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TCGTTAGCATTGTCCT-1320_B04</th>\n",
+       "      <td>TCGTTAGCATTGTCCT</td>\n",
+       "      <td>1320_B04</td>\n",
+       "      <td>L8XR_220630_02_B10</td>\n",
+       "      <td>WMB-10XMulti</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10xRSeq_Mult</td>\n",
+       "      <td>OLF</td>\n",
+       "      <td>C57BL6J-625156</td>\n",
+       "      <td>wt/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>278 NLL Gata3 Gly-Gaba</td>\n",
+       "      <td>1076 NLL Gata3 Gly-Gaba_3</td>\n",
+       "      <td>4806 NLL Gata3 Gly-Gaba_3</td>\n",
+       "      <td>#820e57</td>\n",
+       "      <td>#72195a</td>\n",
+       "      <td>#E57300</td>\n",
+       "      <td>#76CC00</td>\n",
+       "      <td>#FF00CA</td>\n",
+       "      <td>13</td>\n",
+       "      <td>#FF7373</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4042976 rows × 27 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               cell_barcode barcoded_cell_sample_label   \n",
+       "cell_label                                                               \n",
+       "GCGAGAAGTTAAGGGC-410_B05   GCGAGAAGTTAAGGGC                    410_B05  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06   AATGGCTCAGCTCCTT                    411_B06   \n",
+       "AACACACGTTGCTTGA-410_B05   AACACACGTTGCTTGA                    410_B05   \n",
+       "CACAGATAGAGGCGGA-410_A05   CACAGATAGAGGCGGA                    410_A05   \n",
+       "AAAGTGAAGCATTTCG-410_B05   AAAGTGAAGCATTTCG                    410_B05   \n",
+       "...                                     ...                        ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05  GTGTGAGCAAACGCGA                   1350_C05   \n",
+       "TTAGCAATCCCTGTTA-1350_C05  TTAGCAATCCCTGTTA                   1350_C05   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05  TTTGGCTGTCGCGCAA                   1350_C05   \n",
+       "ATCCACCTCACAGACT-1320_B04  ATCCACCTCACAGACT                   1320_B04   \n",
+       "TCGTTAGCATTGTCCT-1320_B04  TCGTTAGCATTGTCCT                   1320_B04   \n",
+       "\n",
+       "                                library_label feature_matrix_label entity   \n",
+       "cell_label                                                                  \n",
+       "GCGAGAAGTTAAGGGC-410_B05   L8TX_201030_01_C12        WMB-10Xv3-HPF   cell  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06   L8TX_201029_01_E10        WMB-10Xv3-HPF   cell   \n",
+       "AACACACGTTGCTTGA-410_B05   L8TX_201030_01_C12        WMB-10Xv3-HPF   cell   \n",
+       "CACAGATAGAGGCGGA-410_A05   L8TX_201029_01_A10        WMB-10Xv3-HPF   cell   \n",
+       "AAAGTGAAGCATTTCG-410_B05   L8TX_201030_01_C12        WMB-10Xv3-HPF   cell   \n",
+       "...                                       ...                  ...    ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05  L8XR_220728_01_A05         WMB-10XMulti   cell   \n",
+       "TTAGCAATCCCTGTTA-1350_C05  L8XR_220728_01_A05         WMB-10XMulti   cell   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05  L8XR_220728_01_A05         WMB-10XMulti   cell   \n",
+       "ATCCACCTCACAGACT-1320_B04  L8XR_220630_02_B10         WMB-10XMulti   cell   \n",
+       "TCGTTAGCATTGTCCT-1320_B04  L8XR_220630_02_B10         WMB-10XMulti   cell   \n",
+       "\n",
+       "                           brain_section_label library_method   \n",
+       "cell_label                                                      \n",
+       "GCGAGAAGTTAAGGGC-410_B05                   NaN          10Xv3  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06                   NaN          10Xv3   \n",
+       "AACACACGTTGCTTGA-410_B05                   NaN          10Xv3   \n",
+       "CACAGATAGAGGCGGA-410_A05                   NaN          10Xv3   \n",
+       "AAAGTGAAGCATTTCG-410_B05                   NaN          10Xv3   \n",
+       "...                                        ...            ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05                  NaN   10xRSeq_Mult   \n",
+       "TTAGCAATCCCTGTTA-1350_C05                  NaN   10xRSeq_Mult   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05                  NaN   10xRSeq_Mult   \n",
+       "ATCCACCTCACAGACT-1320_B04                  NaN   10xRSeq_Mult   \n",
+       "TCGTTAGCATTGTCCT-1320_B04                  NaN   10xRSeq_Mult   \n",
+       "\n",
+       "                          region_of_interest_acronym   \n",
+       "cell_label                                             \n",
+       "GCGAGAAGTTAAGGGC-410_B05                         RHP  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06                         RHP   \n",
+       "AACACACGTTGCTTGA-410_B05                         RHP   \n",
+       "CACAGATAGAGGCGGA-410_A05                         RHP   \n",
+       "AAAGTGAAGCATTTCG-410_B05                         RHP   \n",
+       "...                                              ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05                         MB   \n",
+       "TTAGCAATCCCTGTTA-1350_C05                         MB   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05                         MB   \n",
+       "ATCCACCTCACAGACT-1320_B04                        OLF   \n",
+       "TCGTTAGCATTGTCCT-1320_B04                        OLF   \n",
+       "\n",
+       "                                            donor_label    donor_genotype   \n",
+       "cell_label                                                                  \n",
+       "GCGAGAAGTTAAGGGC-410_B05   Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06   Snap25-IRES2-Cre;Ai14-550851  Ai14(RCL-tdT)/wt   \n",
+       "AACACACGTTGCTTGA-410_B05   Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt   \n",
+       "CACAGATAGAGGCGGA-410_A05   Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt   \n",
+       "AAAGTGAAGCATTTCG-410_B05   Snap25-IRES2-Cre;Ai14-550850  Ai14(RCL-tdT)/wt   \n",
+       "...                                                 ...               ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05                C57BL6J-641405             wt/wt   \n",
+       "TTAGCAATCCCTGTTA-1350_C05                C57BL6J-641405             wt/wt   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05                C57BL6J-641405             wt/wt   \n",
+       "ATCCACCTCACAGACT-1320_B04                C57BL6J-625156             wt/wt   \n",
+       "TCGTTAGCATTGTCCT-1320_B04                C57BL6J-625156             wt/wt   \n",
+       "\n",
+       "                           ...                subclass   \n",
+       "cell_label                 ...                           \n",
+       "GCGAGAAGTTAAGGGC-410_B05   ...  018 L2 IT PPP-APr Glut  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06   ...  018 L2 IT PPP-APr Glut   \n",
+       "AACACACGTTGCTTGA-410_B05   ...  018 L2 IT PPP-APr Glut   \n",
+       "CACAGATAGAGGCGGA-410_A05   ...  018 L2 IT PPP-APr Glut   \n",
+       "AAAGTGAAGCATTTCG-410_B05   ...  018 L2 IT PPP-APr Glut   \n",
+       "...                        ...                     ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05  ...  278 NLL Gata3 Gly-Gaba   \n",
+       "TTAGCAATCCCTGTTA-1350_C05  ...        157 RN Spp1 Glut   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05  ...  278 NLL Gata3 Gly-Gaba   \n",
+       "ATCCACCTCACAGACT-1320_B04  ...  278 NLL Gata3 Gly-Gaba   \n",
+       "TCGTTAGCATTGTCCT-1320_B04  ...  278 NLL Gata3 Gly-Gaba   \n",
+       "\n",
+       "                                           supertype   \n",
+       "cell_label                                             \n",
+       "GCGAGAAGTTAAGGGC-410_B05   0082 L2 IT PPP-APr Glut_3  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06   0082 L2 IT PPP-APr Glut_3   \n",
+       "AACACACGTTGCTTGA-410_B05   0082 L2 IT PPP-APr Glut_3   \n",
+       "CACAGATAGAGGCGGA-410_A05   0082 L2 IT PPP-APr Glut_3   \n",
+       "AAAGTGAAGCATTTCG-410_B05   0082 L2 IT PPP-APr Glut_3   \n",
+       "...                                              ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05  1074 NLL Gata3 Gly-Gaba_1   \n",
+       "TTAGCAATCCCTGTTA-1350_C05        0682 RN Spp1 Glut_1   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05  1076 NLL Gata3 Gly-Gaba_3   \n",
+       "ATCCACCTCACAGACT-1320_B04  1076 NLL Gata3 Gly-Gaba_3   \n",
+       "TCGTTAGCATTGTCCT-1320_B04  1076 NLL Gata3 Gly-Gaba_3   \n",
+       "\n",
+       "                                             cluster  neurotransmitter_color   \n",
+       "cell_label                                                                     \n",
+       "GCGAGAAGTTAAGGGC-410_B05   0326 L2 IT PPP-APr Glut_3                 #2B93DF  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06   0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "AACACACGTTGCTTGA-410_B05   0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "CACAGATAGAGGCGGA-410_A05   0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "AAAGTGAAGCATTTCG-410_B05   0326 L2 IT PPP-APr Glut_3                 #2B93DF   \n",
+       "...                                              ...                     ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05  4804 NLL Gata3 Gly-Gaba_1                 #820e57   \n",
+       "TTAGCAATCCCTGTTA-1350_C05        2761 RN Spp1 Glut_1                 #2B93DF   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05  4806 NLL Gata3 Gly-Gaba_3                 #820e57   \n",
+       "ATCCACCTCACAGACT-1320_B04  4806 NLL Gata3 Gly-Gaba_3                 #820e57   \n",
+       "TCGTTAGCATTGTCCT-1320_B04  4806 NLL Gata3 Gly-Gaba_3                 #820e57   \n",
+       "\n",
+       "                           class_color subclass_color supertype_color   \n",
+       "cell_label                                                              \n",
+       "GCGAGAAGTTAAGGGC-410_B05       #FA0087        #0F6632         #266DFF  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06       #FA0087        #0F6632         #266DFF   \n",
+       "AACACACGTTGCTTGA-410_B05       #FA0087        #0F6632         #266DFF   \n",
+       "CACAGATAGAGGCGGA-410_A05       #FA0087        #0F6632         #266DFF   \n",
+       "AAAGTGAAGCATTTCG-410_B05       #FA0087        #0F6632         #266DFF   \n",
+       "...                                ...            ...             ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05      #72195a        #E57300         #a4fcb2   \n",
+       "TTAGCAATCCCTGTTA-1350_C05      #007200        #FF514D         #BA1FCC   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05      #72195a        #E57300         #76CC00   \n",
+       "ATCCACCTCACAGACT-1320_B04      #72195a        #E57300         #76CC00   \n",
+       "TCGTTAGCATTGTCCT-1320_B04      #72195a        #E57300         #76CC00   \n",
+       "\n",
+       "                          cluster_color region_of_interest_order   \n",
+       "cell_label                                                         \n",
+       "GCGAGAAGTTAAGGGC-410_B05        #64661F                       15  \\\n",
+       "AATGGCTCAGCTCCTT-411_B06        #64661F                       15   \n",
+       "AACACACGTTGCTTGA-410_B05        #64661F                       15   \n",
+       "CACAGATAGAGGCGGA-410_A05        #64661F                       15   \n",
+       "AAAGTGAAGCATTTCG-410_B05        #64661F                       15   \n",
+       "...                                 ...                      ...   \n",
+       "GTGTGAGCAAACGCGA-1350_C05       #C7CC7A                       25   \n",
+       "TTAGCAATCCCTGTTA-1350_C05       #3DCC44                       25   \n",
+       "TTTGGCTGTCGCGCAA-1350_C05       #FF00CA                       25   \n",
+       "ATCCACCTCACAGACT-1320_B04       #FF00CA                       13   \n",
+       "TCGTTAGCATTGTCCT-1320_B04       #FF00CA                       13   \n",
+       "\n",
+       "                          region_of_interest_color  \n",
+       "cell_label                                          \n",
+       "GCGAGAAGTTAAGGGC-410_B05                   #CCB05C  \n",
+       "AATGGCTCAGCTCCTT-411_B06                   #CCB05C  \n",
+       "AACACACGTTGCTTGA-410_B05                   #CCB05C  \n",
+       "CACAGATAGAGGCGGA-410_A05                   #CCB05C  \n",
+       "AAAGTGAAGCATTTCG-410_B05                   #CCB05C  \n",
+       "...                                            ...  \n",
+       "GTGTGAGCAAACGCGA-1350_C05                  #CC5CB0  \n",
+       "TTAGCAATCCCTGTTA-1350_C05                  #CC5CB0  \n",
+       "TTTGGCTGTCGCGCAA-1350_C05                  #CC5CB0  \n",
+       "ATCCACCTCACAGACT-1320_B04                  #FF7373  \n",
+       "TCGTTAGCATTGTCCT-1320_B04                  #FF7373  \n",
+       "\n",
+       "[4042976 rows x 27 columns]"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell_extended"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>barcoded_cell_sample_label</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>feature_matrix_label</th>\n",
+       "      <th>entity</th>\n",
+       "      <th>brain_section_label</th>\n",
+       "      <th>library_method</th>\n",
+       "      <th>region_of_interest_acronym</th>\n",
+       "      <th>donor_label</th>\n",
+       "      <th>donor_genotype</th>\n",
+       "      <th>...</th>\n",
+       "      <th>subclass</th>\n",
+       "      <th>supertype</th>\n",
+       "      <th>cluster</th>\n",
+       "      <th>neurotransmitter_color</th>\n",
+       "      <th>class_color</th>\n",
+       "      <th>subclass_color</th>\n",
+       "      <th>supertype_color</th>\n",
+       "      <th>cluster_color</th>\n",
+       "      <th>region_of_interest_order</th>\n",
+       "      <th>region_of_interest_color</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cell_label</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>CAGGTGCAGGCTAGCA-040_C01</th>\n",
+       "      <td>CAGGTGCAGGCTAGCA</td>\n",
+       "      <td>040_C01</td>\n",
+       "      <td>L8TX_180815_01_E08</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-404124</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>078 SI-MA-ACB Ebf1 Bnc2 Gaba</td>\n",
+       "      <td>0366 SI-MA-ACB Ebf1 Bnc2 Gaba_3</td>\n",
+       "      <td>1324 SI-MA-ACB Ebf1 Bnc2 Gaba_3</td>\n",
+       "      <td>#FF3358</td>\n",
+       "      <td>#450099</td>\n",
+       "      <td>#5CBCCC</td>\n",
+       "      <td>#38662E</td>\n",
+       "      <td>#5C7ECC</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TGCGCAGGTTGCGCAC-045_C01</th>\n",
+       "      <td>TGCGCAGGTTGCGCAC</td>\n",
+       "      <td>045_C01</td>\n",
+       "      <td>L8TX_180829_01_C10</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-407905</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>097 PVHd-SBPV Six3 Prox1 Gaba</td>\n",
+       "      <td>0442 PVHd-SBPV Six3 Prox1 Gaba_1</td>\n",
+       "      <td>1632 PVHd-SBPV Six3 Prox1 Gaba_1</td>\n",
+       "      <td>#FF3358</td>\n",
+       "      <td>#FF6600</td>\n",
+       "      <td>#2E3D66</td>\n",
+       "      <td>#9D7ACC</td>\n",
+       "      <td>#FFD600</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CGATGTATCTTGCCGT-042_B01</th>\n",
+       "      <td>CGATGTATCTTGCCGT</td>\n",
+       "      <td>042_B01</td>\n",
+       "      <td>L8TX_180829_01_B09</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-407901</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>203 LGv-SPFp-SPFm Nkx2-2 Tcf7l2 Gaba</td>\n",
+       "      <td>0837 LGv-SPFp-SPFm Nkx2-2 Tcf7l2 Gaba_4</td>\n",
+       "      <td>3657 LGv-SPFp-SPFm Nkx2-2 Tcf7l2 Gaba_4</td>\n",
+       "      <td>#FF3358</td>\n",
+       "      <td>#9EF01A</td>\n",
+       "      <td>#FFC199</td>\n",
+       "      <td>#460F66</td>\n",
+       "      <td>#7AA0CC</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GACTAACGTCCTCTTG-040_B01</th>\n",
+       "      <td>GACTAACGTCCTCTTG</td>\n",
+       "      <td>040_B01</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-404124</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>096 PVHd Gsc Gaba</td>\n",
+       "      <td>0441 PVHd Gsc Gaba_1</td>\n",
+       "      <td>1625 PVHd Gsc Gaba_1</td>\n",
+       "      <td>#FF3358</td>\n",
+       "      <td>#FF6600</td>\n",
+       "      <td>#3B1FCC</td>\n",
+       "      <td>#854599</td>\n",
+       "      <td>#2E6663</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GATCGTACAACTGCTA-040_B01</th>\n",
+       "      <td>GATCGTACAACTGCTA</td>\n",
+       "      <td>040_B01</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-404124</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>096 PVHd Gsc Gaba</td>\n",
+       "      <td>0441 PVHd Gsc Gaba_1</td>\n",
+       "      <td>1625 PVHd Gsc Gaba_1</td>\n",
+       "      <td>#FF3358</td>\n",
+       "      <td>#FF6600</td>\n",
+       "      <td>#3B1FCC</td>\n",
+       "      <td>#854599</td>\n",
+       "      <td>#2E6663</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTACTCCGTAGTACCT-103_B01</th>\n",
+       "      <td>GTACTCCGTAGTACCT</td>\n",
+       "      <td>103_B01</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>333 Endo NN</td>\n",
+       "      <td>1193 Endo NN_1</td>\n",
+       "      <td>5310 Endo NN_1</td>\n",
+       "      <td>#666666</td>\n",
+       "      <td>#858881</td>\n",
+       "      <td>#994567</td>\n",
+       "      <td>#00992A</td>\n",
+       "      <td>#FFB473</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTGAAGGTCAGCTCTC-103_B01</th>\n",
+       "      <td>GTGAAGGTCAGCTCTC</td>\n",
+       "      <td>103_B01</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>333 Endo NN</td>\n",
+       "      <td>1193 Endo NN_1</td>\n",
+       "      <td>5310 Endo NN_1</td>\n",
+       "      <td>#666666</td>\n",
+       "      <td>#858881</td>\n",
+       "      <td>#994567</td>\n",
+       "      <td>#00992A</td>\n",
+       "      <td>#FFB473</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ACACCCTCATGCGCAC-103_C01</th>\n",
+       "      <td>ACACCCTCATGCGCAC</td>\n",
+       "      <td>103_C01</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>333 Endo NN</td>\n",
+       "      <td>1193 Endo NN_1</td>\n",
+       "      <td>5310 Endo NN_1</td>\n",
+       "      <td>#666666</td>\n",
+       "      <td>#858881</td>\n",
+       "      <td>#994567</td>\n",
+       "      <td>#00992A</td>\n",
+       "      <td>#FFB473</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CCTAAAGCAAGAGGCT-103_C01</th>\n",
+       "      <td>CCTAAAGCAAGAGGCT</td>\n",
+       "      <td>103_C01</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>333 Endo NN</td>\n",
+       "      <td>1193 Endo NN_1</td>\n",
+       "      <td>5310 Endo NN_1</td>\n",
+       "      <td>#666666</td>\n",
+       "      <td>#858881</td>\n",
+       "      <td>#994567</td>\n",
+       "      <td>#00992A</td>\n",
+       "      <td>#FFB473</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TCTGGAAAGATGAGAG-103_C01</th>\n",
+       "      <td>TCTGGAAAGATGAGAG</td>\n",
+       "      <td>103_C01</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>333 Endo NN</td>\n",
+       "      <td>1193 Endo NN_1</td>\n",
+       "      <td>5310 Endo NN_1</td>\n",
+       "      <td>#666666</td>\n",
+       "      <td>#858881</td>\n",
+       "      <td>#994567</td>\n",
+       "      <td>#00992A</td>\n",
+       "      <td>#FFB473</td>\n",
+       "      <td>23</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>130555 rows × 27 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              cell_barcode barcoded_cell_sample_label   \n",
+       "cell_label                                                              \n",
+       "CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA                    040_C01  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC                    045_C01   \n",
+       "CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT                    042_B01   \n",
+       "GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG                    040_B01   \n",
+       "GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA                    040_B01   \n",
+       "...                                    ...                        ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT                    103_B01   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC                    103_B01   \n",
+       "ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC                    103_C01   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT                    103_C01   \n",
+       "TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG                    103_C01   \n",
+       "\n",
+       "                               library_label feature_matrix_label entity   \n",
+       "cell_label                                                                 \n",
+       "CAGGTGCAGGCTAGCA-040_C01  L8TX_180815_01_E08         WMB-10Xv2-TH   cell  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  L8TX_180829_01_C10         WMB-10Xv2-TH   cell   \n",
+       "CGATGTATCTTGCCGT-042_B01  L8TX_180829_01_B09         WMB-10Xv2-TH   cell   \n",
+       "GACTAACGTCCTCTTG-040_B01  L8TX_180815_01_D08         WMB-10Xv2-TH   cell   \n",
+       "GATCGTACAACTGCTA-040_B01  L8TX_180815_01_D08         WMB-10Xv2-TH   cell   \n",
+       "...                                      ...                  ...    ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  L8TX_190321_01_G03         WMB-10Xv2-TH   cell   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  L8TX_190321_01_G03         WMB-10Xv2-TH   cell   \n",
+       "ACACCCTCATGCGCAC-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+       "TCTGGAAAGATGAGAG-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+       "\n",
+       "                          brain_section_label library_method   \n",
+       "cell_label                                                     \n",
+       "CAGGTGCAGGCTAGCA-040_C01                  NaN          10Xv2  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                  NaN          10Xv2   \n",
+       "CGATGTATCTTGCCGT-042_B01                  NaN          10Xv2   \n",
+       "GACTAACGTCCTCTTG-040_B01                  NaN          10Xv2   \n",
+       "GATCGTACAACTGCTA-040_B01                  NaN          10Xv2   \n",
+       "...                                       ...            ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                  NaN          10Xv2   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                  NaN          10Xv2   \n",
+       "ACACCCTCATGCGCAC-103_C01                  NaN          10Xv2   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                  NaN          10Xv2   \n",
+       "TCTGGAAAGATGAGAG-103_C01                  NaN          10Xv2   \n",
+       "\n",
+       "                         region_of_interest_acronym   \n",
+       "cell_label                                            \n",
+       "CAGGTGCAGGCTAGCA-040_C01                         TH  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                         TH   \n",
+       "CGATGTATCTTGCCGT-042_B01                         TH   \n",
+       "GACTAACGTCCTCTTG-040_B01                         TH   \n",
+       "GATCGTACAACTGCTA-040_B01                         TH   \n",
+       "...                                             ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                         TH   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                         TH   \n",
+       "ACACCCTCATGCGCAC-103_C01                         TH   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                         TH   \n",
+       "TCTGGAAAGATGAGAG-103_C01                         TH   \n",
+       "\n",
+       "                                           donor_label   \n",
+       "cell_label                                               \n",
+       "CAGGTGCAGGCTAGCA-040_C01  Snap25-IRES2-Cre;Ai14-404124  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  Snap25-IRES2-Cre;Ai14-407905   \n",
+       "CGATGTATCTTGCCGT-042_B01  Snap25-IRES2-Cre;Ai14-407901   \n",
+       "GACTAACGTCCTCTTG-040_B01  Snap25-IRES2-Cre;Ai14-404124   \n",
+       "GATCGTACAACTGCTA-040_B01  Snap25-IRES2-Cre;Ai14-404124   \n",
+       "...                                                ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "ACACCCTCATGCGCAC-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "TCTGGAAAGATGAGAG-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "\n",
+       "                                                donor_genotype  ...   \n",
+       "cell_label                                                      ...   \n",
+       "CAGGTGCAGGCTAGCA-040_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "CGATGTATCTTGCCGT-042_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "GACTAACGTCCTCTTG-040_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "GATCGTACAACTGCTA-040_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "...                                                        ...  ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "ACACCCTCATGCGCAC-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "TCTGGAAAGATGAGAG-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "\n",
+       "                                                      subclass   \n",
+       "cell_label                                                       \n",
+       "CAGGTGCAGGCTAGCA-040_C01          078 SI-MA-ACB Ebf1 Bnc2 Gaba  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01         097 PVHd-SBPV Six3 Prox1 Gaba   \n",
+       "CGATGTATCTTGCCGT-042_B01  203 LGv-SPFp-SPFm Nkx2-2 Tcf7l2 Gaba   \n",
+       "GACTAACGTCCTCTTG-040_B01                     096 PVHd Gsc Gaba   \n",
+       "GATCGTACAACTGCTA-040_B01                     096 PVHd Gsc Gaba   \n",
+       "...                                                        ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                           333 Endo NN   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                           333 Endo NN   \n",
+       "ACACCCTCATGCGCAC-103_C01                           333 Endo NN   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                           333 Endo NN   \n",
+       "TCTGGAAAGATGAGAG-103_C01                           333 Endo NN   \n",
+       "\n",
+       "                                                        supertype   \n",
+       "cell_label                                                          \n",
+       "CAGGTGCAGGCTAGCA-040_C01          0366 SI-MA-ACB Ebf1 Bnc2 Gaba_3  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01         0442 PVHd-SBPV Six3 Prox1 Gaba_1   \n",
+       "CGATGTATCTTGCCGT-042_B01  0837 LGv-SPFp-SPFm Nkx2-2 Tcf7l2 Gaba_4   \n",
+       "GACTAACGTCCTCTTG-040_B01                     0441 PVHd Gsc Gaba_1   \n",
+       "GATCGTACAACTGCTA-040_B01                     0441 PVHd Gsc Gaba_1   \n",
+       "...                                                           ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                           1193 Endo NN_1   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                           1193 Endo NN_1   \n",
+       "ACACCCTCATGCGCAC-103_C01                           1193 Endo NN_1   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                           1193 Endo NN_1   \n",
+       "TCTGGAAAGATGAGAG-103_C01                           1193 Endo NN_1   \n",
+       "\n",
+       "                                                          cluster   \n",
+       "cell_label                                                          \n",
+       "CAGGTGCAGGCTAGCA-040_C01          1324 SI-MA-ACB Ebf1 Bnc2 Gaba_3  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01         1632 PVHd-SBPV Six3 Prox1 Gaba_1   \n",
+       "CGATGTATCTTGCCGT-042_B01  3657 LGv-SPFp-SPFm Nkx2-2 Tcf7l2 Gaba_4   \n",
+       "GACTAACGTCCTCTTG-040_B01                     1625 PVHd Gsc Gaba_1   \n",
+       "GATCGTACAACTGCTA-040_B01                     1625 PVHd Gsc Gaba_1   \n",
+       "...                                                           ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                           5310 Endo NN_1   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                           5310 Endo NN_1   \n",
+       "ACACCCTCATGCGCAC-103_C01                           5310 Endo NN_1   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                           5310 Endo NN_1   \n",
+       "TCTGGAAAGATGAGAG-103_C01                           5310 Endo NN_1   \n",
+       "\n",
+       "                          neurotransmitter_color  class_color subclass_color   \n",
+       "cell_label                                                                     \n",
+       "CAGGTGCAGGCTAGCA-040_C01                 #FF3358      #450099        #5CBCCC  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                 #FF3358      #FF6600        #2E3D66   \n",
+       "CGATGTATCTTGCCGT-042_B01                 #FF3358      #9EF01A        #FFC199   \n",
+       "GACTAACGTCCTCTTG-040_B01                 #FF3358      #FF6600        #3B1FCC   \n",
+       "GATCGTACAACTGCTA-040_B01                 #FF3358      #FF6600        #3B1FCC   \n",
+       "...                                          ...          ...            ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                 #666666      #858881        #994567   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                 #666666      #858881        #994567   \n",
+       "ACACCCTCATGCGCAC-103_C01                 #666666      #858881        #994567   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                 #666666      #858881        #994567   \n",
+       "TCTGGAAAGATGAGAG-103_C01                 #666666      #858881        #994567   \n",
+       "\n",
+       "                         supertype_color cluster_color   \n",
+       "cell_label                                               \n",
+       "CAGGTGCAGGCTAGCA-040_C01         #38662E       #5C7ECC  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01         #9D7ACC       #FFD600   \n",
+       "CGATGTATCTTGCCGT-042_B01         #460F66       #7AA0CC   \n",
+       "GACTAACGTCCTCTTG-040_B01         #854599       #2E6663   \n",
+       "GATCGTACAACTGCTA-040_B01         #854599       #2E6663   \n",
+       "...                                  ...           ...   \n",
+       "GTACTCCGTAGTACCT-103_B01         #00992A       #FFB473   \n",
+       "GTGAAGGTCAGCTCTC-103_B01         #00992A       #FFB473   \n",
+       "ACACCCTCATGCGCAC-103_C01         #00992A       #FFB473   \n",
+       "CCTAAAGCAAGAGGCT-103_C01         #00992A       #FFB473   \n",
+       "TCTGGAAAGATGAGAG-103_C01         #00992A       #FFB473   \n",
+       "\n",
+       "                         region_of_interest_order region_of_interest_color  \n",
+       "cell_label                                                                  \n",
+       "CAGGTGCAGGCTAGCA-040_C01                       23                  #FF00EF  \n",
+       "TGCGCAGGTTGCGCAC-045_C01                       23                  #FF00EF  \n",
+       "CGATGTATCTTGCCGT-042_B01                       23                  #FF00EF  \n",
+       "GACTAACGTCCTCTTG-040_B01                       23                  #FF00EF  \n",
+       "GATCGTACAACTGCTA-040_B01                       23                  #FF00EF  \n",
+       "...                                           ...                      ...  \n",
+       "GTACTCCGTAGTACCT-103_B01                       23                  #FF00EF  \n",
+       "GTGAAGGTCAGCTCTC-103_B01                       23                  #FF00EF  \n",
+       "ACACCCTCATGCGCAC-103_C01                       23                  #FF00EF  \n",
+       "CCTAAAGCAAGAGGCT-103_C01                       23                  #FF00EF  \n",
+       "TCTGGAAAGATGAGAG-103_C01                       23                  #FF00EF  \n",
+       "\n",
+       "[130555 rows x 27 columns]"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell_filtered"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['cell_barcode', 'barcoded_cell_sample_label', 'library_label', 'feature_matrix_label', 'entity', 'brain_section_label', 'library_method', 'region_of_interest_acronym', 'donor_label', 'donor_genotype', 'donor_sex', 'dataset_label', 'x', 'y', 'cluster_alias', 'neurotransmitter', 'class', 'subclass', 'supertype', 'cluster', 'neurotransmitter_color', 'class_color', 'subclass_color', 'supertype_color', 'cluster_color', 'region_of_interest_order', 'region_of_interest_color']\n"
+     ]
+    }
+   ],
+   "source": [
+    "column_names = cell_filtered.columns.tolist()\n",
+    "print(column_names)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example use cases"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this section, we explore two use cases. The first example looks at the expression of nine canonical neurotransmitter transporter genes and the second the expression of gene Tac2.\n",
+    "\n",
+    "To support these use cases, we will create a smaller submatrix (all cells and 10 genes) that read it into memory. *Note this operation takes around 10 seconds*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000037771</th>\n",
+       "      <td>Slc32a1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000070570</th>\n",
+       "      <td>Slc17a7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000039728</th>\n",
+       "      <td>Slc6a5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000030500</th>\n",
+       "      <td>Slc17a6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000055368</th>\n",
+       "      <td>Slc6a2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000019935</th>\n",
+       "      <td>Slc17a8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000025400</th>\n",
+       "      <td>Tac2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000020838</th>\n",
+       "      <td>Slc6a4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000021609</th>\n",
+       "      <td>Slc6a3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000100241</th>\n",
+       "      <td>Slc18a3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   gene_symbol\n",
+       "gene_identifier               \n",
+       "ENSMUSG00000037771     Slc32a1\n",
+       "ENSMUSG00000070570     Slc17a7\n",
+       "ENSMUSG00000039728      Slc6a5\n",
+       "ENSMUSG00000030500     Slc17a6\n",
+       "ENSMUSG00000055368      Slc6a2\n",
+       "ENSMUSG00000019935     Slc17a8\n",
+       "ENSMUSG00000025400        Tac2\n",
+       "ENSMUSG00000020838      Slc6a4\n",
+       "ENSMUSG00000021609      Slc6a3\n",
+       "ENSMUSG00000100241     Slc18a3"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ntgenes = ['Slc17a7','Slc17a6','Slc17a8','Slc32a1','Slc6a5','Slc18a3','Slc6a3','Slc6a4','Slc6a2']\n",
+    "exgenes = ['Tac2']\n",
+    "gnames = ntgenes + exgenes\n",
+    "pred = [x in gnames for x in adata.var.gene_symbol]\n",
+    "gene_filtered = adata.var[pred]\n",
+    "gene_filtered"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['ENSMUSG00000037771', 'ENSMUSG00000070570', 'ENSMUSG00000039728',\n",
+       "       'ENSMUSG00000030500', 'ENSMUSG00000055368', 'ENSMUSG00000019935',\n",
+       "       'ENSMUSG00000025400', 'ENSMUSG00000020838', 'ENSMUSG00000021609',\n",
+       "       'ENSMUSG00000100241'],\n",
+       "      dtype='object', name='gene_identifier')"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gene_filtered.index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  6.684127469000003\n",
+      "AnnData object with n_obs × n_vars = 131212 × 10\n",
+      "    obs: 'cell_barcode', 'library_label', 'anatomical_division_label'\n",
+      "    var: 'gene_symbol'\n",
+      "    uns: 'normalization', 'parent', 'parent_layer', 'parent_rows'\n"
+     ]
+    }
+   ],
+   "source": [
+    "start = time.process_time()\n",
+    "asubset = adata[:,gene_filtered.index].to_memory()\n",
+    "print(\"time taken: \", time.process_time() - start)\n",
+    "print(asubset)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Let's try this with tiledbsoma"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "       soma_joinid     gene_identifier gene_symbol\n",
+      "3835          3835  ENSMUSG00000037771     Slc32a1\n",
+      "12190        12190  ENSMUSG00000070570     Slc17a7\n",
+      "12316        12316  ENSMUSG00000039728      Slc6a5\n",
+      "12321        12321  ENSMUSG00000030500     Slc17a6\n",
+      "14782        14782  ENSMUSG00000055368      Slc6a2\n",
+      "18122        18122  ENSMUSG00000019935     Slc17a8\n",
+      "18521        18521  ENSMUSG00000025400        Tac2\n",
+      "19691        19691  ENSMUSG00000020838      Slc6a4\n",
+      "23107        23107  ENSMUSG00000021609      Slc6a3\n",
+      "23903        23903  ENSMUSG00000100241     Slc18a3\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get the gene symbols of all genes.\n",
+    "gene_symbols_and_identifiers = tdbs.ms[\"RNA\"].var.read().concat().to_pandas()\n",
+    "\n",
+    "# Create a list of genes to filter.\n",
+    "genes_to_filter = [\"Slc17a7\", \"Slc17a6\", \"Slc17a8\", \"Slc32a1\", \"Slc6a5\", \"Slc18a3\", \"Slc6a3\", \"Slc6a4\", \"Slc6a2\", \"Tac2\"]\n",
+    "\n",
+    "# Filter the gene symbols and identifiers based on the list of genes to filter.\n",
+    "filtered_gene_symbols_and_identifiers = gene_symbols_and_identifiers[gene_symbols_and_identifiers[\"gene_symbol\"].isin(genes_to_filter)]\n",
+    "\n",
+    "# Print the filtered gene symbols and identifiers.\n",
+    "print(filtered_gene_symbols_and_identifiers)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The goal is to replicate the behavior of AnnData's subsetting capabilities but using TileDB, specifically to filter a large expression matrix down to specific genes and cells without loading the entire dataset into memory.\n",
+    "\n",
+    "The code for AnnData efficiently selects a subset of the data by columns (genes), but it's important to note that this operation may load the data into memory, as indicated by the .to_memory() method. In contrast, TileDB allows for disk-based slicing, which is beneficial for large datasets that cannot fit in memory.\n",
+    "\n",
+    "Below, you can see how to successfully filter gene symbols and their corresponding soma_joinid using TileDB, which is akin to selecting specific columns in AnnData. To achieve the complete subsetting, here are the steps for TileDB:\n",
+    "\n",
+    "Get the list of soma_joinids corresponding to the genes of interest.\n",
+    "Read only the relevant rows and columns (genes) from TileDB's sparse array, storing them in an efficient in-memory sparse format."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<Experiment '/shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2' (open for 'r') (2 items)\n",
+      "    'ms': Collection 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms' (open for 'r') (1 item)\n",
+      "        'RNA': Measurement 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA' (open for 'r') (3 items)\n",
+      "            'X': Collection 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X' (open for 'r') (1 item)\n",
+      "                'data': SparseNDArray 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X/data' (open for 'r')\n",
+      "            'var': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')\n",
+      "            'uns': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/uns' (unopened)\n",
+      "    'obs': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/obs' (open for 'r')>\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tdbs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<Measurement 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA' (open for 'r') (3 items)\n",
+      "    'X': Collection 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X' (open for 'r') (1 item)\n",
+      "        'data': SparseNDArray 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X/data' (open for 'r')\n",
+      "    'var': DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')\n",
+      "    'uns': 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/uns' (unopened)>\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tdbs.ms[\"RNA\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<SparseNDArray 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X/data' (open for 'r')>\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tdbs.ms[\"RNA\"].X[\"data\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Le'ts do a quick sanity check"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Shape of AnnData object: 131212 32285\n",
+      "131212 32285\n",
+      "The shapes match. Conversion is likely accurate.\n"
+     ]
+    }
+   ],
+   "source": [
+    "n_obs_anndata, n_vars_anndata = adata.shape\n",
+    "print(\"Shape of AnnData object:\", n_obs_anndata, n_vars_anndata)\n",
+    "# Get the shape of the expression data in TileDB\n",
+    "n_obs = len(tdbs.obs)\n",
+    "n_vars = len(tdbs.ms[\"RNA\"].var.read().concat().to_pandas())\n",
+    "print(n_obs, n_vars)\n",
+    "# Check if shapes match\n",
+    "if (n_obs == n_obs_anndata) and (n_vars == n_vars_anndata):\n",
+    "    print(\"The shapes match. Conversion is likely accurate.\")\n",
+    "else:\n",
+    "    print(\"The shapes do not match. Check the conversion steps.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 20.1 s, sys: 28.4 s, total: 48.5 s\n",
+      "Wall time: 6.74 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# Import necessary libraries\n",
+    "from scipy.sparse import vstack\n",
+    "\n",
+    "# Get the shape of the expression data in TileDB\n",
+    "n_obs = len(tdbs.obs)\n",
+    "n_var = len(tdbs.ms[\"RNA\"].var.read().concat().to_pandas())\n",
+    "\n",
+    "# Filter gene symbols and identifiers\n",
+    "genes_to_filter = [\"Slc17a7\", \"Slc17a6\", \"Slc17a8\", \"Slc32a1\", \"Slc6a5\", \"Slc18a3\", \"Slc6a3\", \"Slc6a4\", \"Slc6a2\", \"Tac2\"]\n",
+    "filtered_gene_symbols_and_identifiers = tdbs.ms[\"RNA\"].var.read().concat().to_pandas()\n",
+    "filtered_gene_symbols_and_identifiers = filtered_gene_symbols_and_identifiers[filtered_gene_symbols_and_identifiers[\"gene_symbol\"].isin(genes_to_filter)]\n",
+    "\n",
+    "# List to hold the sparse matrices for each gene\n",
+    "concatenated_data_list = []\n",
+    "\n",
+    "# Fetch each gene's data by its soma_joinid\n",
+    "for soma_joinid in filtered_gene_symbols_and_identifiers['soma_joinid']:\n",
+    "    # Read the specific rows corresponding to the gene's soma_joinid\n",
+    "    single_row = tdbs.ms[\"RNA\"].X[\"data\"].read((slice(None), [soma_joinid])).coos((n_obs, n_var)).concat()\n",
+    "    # Convert the SparseCOOTensor to a scipy.sparse.coo_matrix\n",
+    "    single_row_scipy = single_row.to_scipy()\n",
+    "    # Add the sparse matrix to the list\n",
+    "    concatenated_data_list.append(single_row_scipy)\n",
+    "\n",
+    "# Vertically stack all the sparse matrices to form a single sparse matrix\n",
+    "final_matrix = vstack(concatenated_data_list)\n",
+    "\n",
+    "# Your final_matrix now contains the expression data for the genes you're interested in\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The output is a sparse matrix in Coordinate List (COO) format. In COO format, a sparse matrix is represented by three one-dimensional arrays for the non-zero elements: the row indices, the column indices, and the values themselves. This representation is efficient for sparse matrices where most of the elements are zero.\n",
+    "\n",
+    "Each tuple, for example (0, 3835), specifies the row and column index where a non-zero value exists in the sparse matrix.\n",
+    "The value following the tuple, such as 9.105261, is the actual non-zero value at that position in the matrix.\n",
+    "The row index likely corresponds to a specific observation (cell), and the column index corresponds to a gene (given the nature of single-cell RNA-seq data). The value itself represents a gene expression level (in this case log2 normalized).\n",
+    "\n",
+    "For instance, (0, 3835) 9.105261 means that in the first observation (or cell), the gene corresponding to column index 3835 has an expression level of 9.105261.\n",
+    "\n",
+    "This sparse representation is extremely useful for large datasets like single-cell RNA-seq, where the matrix is mostly zeros. It allows you to work with the data without loading the entire dense matrix into memory, which is both space- and time-efficient."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  (0, 3835)\t9.105261\n",
+      "  (1, 3835)\t7.7246933\n",
+      "  (2, 3835)\t7.578836\n",
+      "  (3, 3835)\t6.765602\n",
+      "  (4, 3835)\t7.6253023\n",
+      "  (5, 3835)\t8.32904\n",
+      "  (6, 3835)\t9.2027\n",
+      "  (7, 3835)\t9.21632\n",
+      "  (8, 3835)\t7.0556145\n",
+      "  (24, 3835)\t9.412479\n",
+      "  (26, 3835)\t7.567689\n",
+      "  (27, 3835)\t9.002355\n",
+      "  (28, 3835)\t8.746652\n",
+      "  (29, 3835)\t8.885681\n",
+      "  (30, 3835)\t7.4665504\n",
+      "  (32, 3835)\t10.410592\n",
+      "  (33, 3835)\t8.873277\n",
+      "  (35, 3835)\t8.959934\n",
+      "  (36, 3835)\t8.876245\n",
+      "  (37, 3835)\t8.91864\n",
+      "  (38, 3835)\t8.695692\n",
+      "  (39, 3835)\t9.1340475\n",
+      "  (40, 3835)\t8.002409\n",
+      "  (41, 3835)\t8.675711\n",
+      "  (42, 3835)\t8.235202\n",
+      "  :\t:\n",
+      "  (1242226, 23903)\t7.107989\n",
+      "  (1243821, 23903)\t7.1930594\n",
+      "  (1246148, 23903)\t8.492636\n",
+      "  (1249902, 23903)\t6.7659106\n",
+      "  (1250251, 23903)\t9.163217\n",
+      "  (1251693, 23903)\t5.4454265\n",
+      "  (1253308, 23903)\t7.551799\n",
+      "  (1253682, 23903)\t7.0575066\n",
+      "  (1255456, 23903)\t6.3069525\n",
+      "  (1256157, 23903)\t5.9635305\n",
+      "  (1256290, 23903)\t5.4826527\n",
+      "  (1259647, 23903)\t5.908243\n",
+      "  (1263868, 23903)\t6.2600813\n",
+      "  (1263888, 23903)\t5.76369\n",
+      "  (1264734, 23903)\t5.6157503\n",
+      "  (1266449, 23903)\t4.685713\n",
+      "  (1266793, 23903)\t5.697473\n",
+      "  (1276496, 23903)\t5.221981\n",
+      "  (1282674, 23903)\t5.219739\n",
+      "  (1282876, 23903)\t5.3812323\n",
+      "  (1288298, 23903)\t6.785778\n",
+      "  (1289678, 23903)\t7.913464\n",
+      "  (1292824, 23903)\t8.062761\n",
+      "  (1297213, 23903)\t7.179176\n",
+      "  (1300542, 23903)\t7.867638\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(final_matrix)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One of the cool things about tiledb is that you can do querying on the data without loading it.\n",
+    "You can read the documentation for more information: https://tiledbsoma.readthedocs.io/en/latest/_autosummary/tiledbsoma.AxisQuery.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<somacore.query.query.ExperimentAxisQuery at 0x7f322dcc9b50>"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Define your filter criteria for genes\n",
+    "var_query_filter = 'gene_symbol in [\"Slc17a7\", \"Slc17a6\", \"Slc17a8\", \"Slc32a1\", \"Slc6a5\", \"Slc18a3\", \"Slc6a3\", \"Slc6a4\", \"Slc6a2\", \"Tac2\"]'\n",
+    "\n",
+    "# Create the query for RNA measurement, filtering only on the variables (genes)\n",
+    "query = tdbs.axis_query(\n",
+    "    measurement_name=\"RNA\",\n",
+    "    var_query=tiledbsoma.AxisQuery(value_filter=var_query_filter)\n",
+    ")\n",
+    "query"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "131212"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.n_obs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.n_vars"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can simply turn ``obs`` and ``var`` to pandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>cell_label</th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>anatomical_division_label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA-040_C01</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA</td>\n",
+       "      <td>L8TX_180815_01_E08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC-045_C01</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC</td>\n",
+       "      <td>L8TX_180829_01_C10</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>CGATGTATCTTGCCGT-042_B01</td>\n",
+       "      <td>CGATGTATCTTGCCGT</td>\n",
+       "      <td>L8TX_180829_01_B09</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>GACTAACGTCCTCTTG-040_B01</td>\n",
+       "      <td>GACTAACGTCCTCTTG</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GATCGTACAACTGCTA-040_B01</td>\n",
+       "      <td>GATCGTACAACTGCTA</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131207</th>\n",
+       "      <td>131207</td>\n",
+       "      <td>GTACTCCGTAGTACCT-103_B01</td>\n",
+       "      <td>GTACTCCGTAGTACCT</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131208</th>\n",
+       "      <td>131208</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC-103_B01</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131209</th>\n",
+       "      <td>131209</td>\n",
+       "      <td>ACACCCTCATGCGCAC-103_C01</td>\n",
+       "      <td>ACACCCTCATGCGCAC</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131210</th>\n",
+       "      <td>131210</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT-103_C01</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131211</th>\n",
+       "      <td>131211</td>\n",
+       "      <td>TCTGGAAAGATGAGAG-103_C01</td>\n",
+       "      <td>TCTGGAAAGATGAGAG</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>131212 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        soma_joinid                cell_label      cell_barcode   \n",
+       "0                 0  CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA  \\\n",
+       "1                 1  TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC   \n",
+       "2                 2  CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT   \n",
+       "3                 3  GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG   \n",
+       "4                 4  GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA   \n",
+       "...             ...                       ...               ...   \n",
+       "131207       131207  GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT   \n",
+       "131208       131208  GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC   \n",
+       "131209       131209  ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC   \n",
+       "131210       131210  CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT   \n",
+       "131211       131211  TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG   \n",
+       "\n",
+       "             library_label anatomical_division_label  \n",
+       "0       L8TX_180815_01_E08                        TH  \n",
+       "1       L8TX_180829_01_C10                        TH  \n",
+       "2       L8TX_180829_01_B09                        TH  \n",
+       "3       L8TX_180815_01_D08                        TH  \n",
+       "4       L8TX_180815_01_D08                        TH  \n",
+       "...                    ...                       ...  \n",
+       "131207  L8TX_190321_01_G03                        TH  \n",
+       "131208  L8TX_190321_01_G03                        TH  \n",
+       "131209  L8TX_190321_01_H03                        TH  \n",
+       "131210  L8TX_190321_01_H03                        TH  \n",
+       "131211  L8TX_190321_01_H03                        TH  \n",
+       "\n",
+       "[131212 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.obs().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3835</td>\n",
+       "      <td>ENSMUSG00000037771</td>\n",
+       "      <td>Slc32a1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12190</td>\n",
+       "      <td>ENSMUSG00000070570</td>\n",
+       "      <td>Slc17a7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>12316</td>\n",
+       "      <td>ENSMUSG00000039728</td>\n",
+       "      <td>Slc6a5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12321</td>\n",
+       "      <td>ENSMUSG00000030500</td>\n",
+       "      <td>Slc17a6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>14782</td>\n",
+       "      <td>ENSMUSG00000055368</td>\n",
+       "      <td>Slc6a2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>18122</td>\n",
+       "      <td>ENSMUSG00000019935</td>\n",
+       "      <td>Slc17a8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>18521</td>\n",
+       "      <td>ENSMUSG00000025400</td>\n",
+       "      <td>Tac2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>19691</td>\n",
+       "      <td>ENSMUSG00000020838</td>\n",
+       "      <td>Slc6a4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>23107</td>\n",
+       "      <td>ENSMUSG00000021609</td>\n",
+       "      <td>Slc6a3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>23903</td>\n",
+       "      <td>ENSMUSG00000100241</td>\n",
+       "      <td>Slc18a3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   soma_joinid     gene_identifier gene_symbol\n",
+       "0         3835  ENSMUSG00000037771     Slc32a1\n",
+       "1        12190  ENSMUSG00000070570     Slc17a7\n",
+       "2        12316  ENSMUSG00000039728      Slc6a5\n",
+       "3        12321  ENSMUSG00000030500     Slc17a6\n",
+       "4        14782  ENSMUSG00000055368      Slc6a2\n",
+       "5        18122  ENSMUSG00000019935     Slc17a8\n",
+       "6        18521  ENSMUSG00000025400        Tac2\n",
+       "7        19691  ENSMUSG00000020838      Slc6a4\n",
+       "8        23107  ENSMUSG00000021609      Slc6a3\n",
+       "9        23903  ENSMUSG00000100241     Slc18a3"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.var().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['ENSMUSG00000037771', 'ENSMUSG00000070570', 'ENSMUSG00000039728', 'ENSMUSG00000030500', 'ENSMUSG00000055368', 'ENSMUSG00000019935', 'ENSMUSG00000025400', 'ENSMUSG00000020838', 'ENSMUSG00000021609', 'ENSMUSG00000100241']\n",
+      "[3835, 12190, 12316, 12321, 14782, 18122, 18521, 19691, 23107, 23903]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# List of gene identifiers you're interested in\n",
+    "filtered_gene_identifiers = filtered_gene_symbols_and_identifiers['gene_identifier'].tolist()\n",
+    "print(filtered_gene_identifiers)\n",
+    "filtered_gene_indices = filtered_gene_symbols_and_identifiers['soma_joinid'].tolist()\n",
+    "print(filtered_gene_indices)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can also do AxisQuery filtering on the Experiment.\n",
+    "\n",
+    "ExperimentAxisQuery allows easy selection and extraction of data from a single Measurement in an Experiment, by obs/var (axis) coordinates and/or value filter.\n",
+    "\n",
+    "The primary use for this class is slicing Experiment X layers by obs or var value and/or coordinates. Slicing on SparseNDArray X matrices is supported; DenseNDArray is not supported at this time.\n",
+    "Read the documentation for more information: https://tiledbsoma.readthedocs.io/en/latest/_autosummary/tiledbsoma.ExperimentAxisQuery.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<somacore.query.query.ExperimentAxisQuery object at 0x7f32cb186790>\n",
+      "Time taken: 0.0003514530000074956\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Build the query\n",
+    "query = tiledbsoma.ExperimentAxisQuery(\n",
+    "    experiment=tdbs,  # Assuming tdbs is your Experiment object\n",
+    "    measurement_name=\"RNA\",\n",
+    "    var_query=tiledbsoma.AxisQuery(\n",
+    "        value_filter=f\"soma_joinid in {filtered_gene_indices}\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "# Measure time taken to fetch the subset\n",
+    "start_time = time.process_time()\n",
+    "print(query)\n",
+    "end_time = time.process_time()\n",
+    "\n",
+    "# Output the time taken\n",
+    "print(f\"Time taken: {end_time - start_time}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>cell_label</th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>anatomical_division_label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA-040_C01</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA</td>\n",
+       "      <td>L8TX_180815_01_E08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC-045_C01</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC</td>\n",
+       "      <td>L8TX_180829_01_C10</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>CGATGTATCTTGCCGT-042_B01</td>\n",
+       "      <td>CGATGTATCTTGCCGT</td>\n",
+       "      <td>L8TX_180829_01_B09</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>GACTAACGTCCTCTTG-040_B01</td>\n",
+       "      <td>GACTAACGTCCTCTTG</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GATCGTACAACTGCTA-040_B01</td>\n",
+       "      <td>GATCGTACAACTGCTA</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131207</th>\n",
+       "      <td>131207</td>\n",
+       "      <td>GTACTCCGTAGTACCT-103_B01</td>\n",
+       "      <td>GTACTCCGTAGTACCT</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131208</th>\n",
+       "      <td>131208</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC-103_B01</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131209</th>\n",
+       "      <td>131209</td>\n",
+       "      <td>ACACCCTCATGCGCAC-103_C01</td>\n",
+       "      <td>ACACCCTCATGCGCAC</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131210</th>\n",
+       "      <td>131210</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT-103_C01</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131211</th>\n",
+       "      <td>131211</td>\n",
+       "      <td>TCTGGAAAGATGAGAG-103_C01</td>\n",
+       "      <td>TCTGGAAAGATGAGAG</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>131212 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        soma_joinid                cell_label      cell_barcode   \n",
+       "0                 0  CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA  \\\n",
+       "1                 1  TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC   \n",
+       "2                 2  CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT   \n",
+       "3                 3  GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG   \n",
+       "4                 4  GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA   \n",
+       "...             ...                       ...               ...   \n",
+       "131207       131207  GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT   \n",
+       "131208       131208  GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC   \n",
+       "131209       131209  ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC   \n",
+       "131210       131210  CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT   \n",
+       "131211       131211  TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG   \n",
+       "\n",
+       "             library_label anatomical_division_label  \n",
+       "0       L8TX_180815_01_E08                        TH  \n",
+       "1       L8TX_180829_01_C10                        TH  \n",
+       "2       L8TX_180829_01_B09                        TH  \n",
+       "3       L8TX_180815_01_D08                        TH  \n",
+       "4       L8TX_180815_01_D08                        TH  \n",
+       "...                    ...                       ...  \n",
+       "131207  L8TX_190321_01_G03                        TH  \n",
+       "131208  L8TX_190321_01_G03                        TH  \n",
+       "131209  L8TX_190321_01_H03                        TH  \n",
+       "131210  L8TX_190321_01_H03                        TH  \n",
+       "131211  L8TX_190321_01_H03                        TH  \n",
+       "\n",
+       "[131212 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# access the `DataFrame` containing the annotations for all cells that passed the filter using the `.obs` property.\n",
+    "query.obs().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Note that since we ran the query on soma_joinid,\n",
+    "```query.var().concat().to_pandas()``` will return an error:\n",
+    "```RuntimeError: TileDBError: `soma_joinid` is a dimension. QueryConditions currently only work on attributes.```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Let's get back to our complex query"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<somacore.query.query.ExperimentAxisQuery object at 0x7f322dc87110>\n",
+      "Time taken: 0.00026583999999729713\n"
+     ]
+    }
+   ],
+   "source": [
+    "# List of gene symbols you're interested in\n",
+    "filtered_gene_symbols = [\"Slc17a7\", \"Slc17a6\", \"Slc17a8\", \"Slc32a1\", \"Slc6a5\", \"Slc18a3\", \"Slc6a3\", \"Slc6a4\", \"Slc6a2\", \"Tac2\"]\n",
+    "\n",
+    "# Build the query\n",
+    "query = tiledbsoma.ExperimentAxisQuery(\n",
+    "    experiment=tdbs,  # tdbs is your Experiment object\n",
+    "    measurement_name=\"RNA\",\n",
+    "    var_query=tiledbsoma.AxisQuery(\n",
+    "        value_filter=f\"gene_symbol in {filtered_gene_symbols}\",\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "# Measure time taken to fetch the subset\n",
+    "start_time = time.process_time()\n",
+    "print(query)\n",
+    "end_time = time.process_time()\n",
+    "\n",
+    "# Output the time taken\n",
+    "print(f\"Time taken: {end_time - start_time}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of variables: 10\n",
+      "Number of observations: 131212\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Access the number of variables (genes) and observations (cells) in the query\n",
+    "print(\"Number of variables:\", query.n_vars)\n",
+    "print(\"Number of observations:\", query.n_obs)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>cell_label</th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>anatomical_division_label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA-040_C01</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA</td>\n",
+       "      <td>L8TX_180815_01_E08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC-045_C01</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC</td>\n",
+       "      <td>L8TX_180829_01_C10</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>CGATGTATCTTGCCGT-042_B01</td>\n",
+       "      <td>CGATGTATCTTGCCGT</td>\n",
+       "      <td>L8TX_180829_01_B09</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>GACTAACGTCCTCTTG-040_B01</td>\n",
+       "      <td>GACTAACGTCCTCTTG</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GATCGTACAACTGCTA-040_B01</td>\n",
+       "      <td>GATCGTACAACTGCTA</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131207</th>\n",
+       "      <td>131207</td>\n",
+       "      <td>GTACTCCGTAGTACCT-103_B01</td>\n",
+       "      <td>GTACTCCGTAGTACCT</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131208</th>\n",
+       "      <td>131208</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC-103_B01</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131209</th>\n",
+       "      <td>131209</td>\n",
+       "      <td>ACACCCTCATGCGCAC-103_C01</td>\n",
+       "      <td>ACACCCTCATGCGCAC</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131210</th>\n",
+       "      <td>131210</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT-103_C01</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131211</th>\n",
+       "      <td>131211</td>\n",
+       "      <td>TCTGGAAAGATGAGAG-103_C01</td>\n",
+       "      <td>TCTGGAAAGATGAGAG</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>131212 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        soma_joinid                cell_label      cell_barcode   \n",
+       "0                 0  CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA  \\\n",
+       "1                 1  TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC   \n",
+       "2                 2  CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT   \n",
+       "3                 3  GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG   \n",
+       "4                 4  GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA   \n",
+       "...             ...                       ...               ...   \n",
+       "131207       131207  GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT   \n",
+       "131208       131208  GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC   \n",
+       "131209       131209  ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC   \n",
+       "131210       131210  CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT   \n",
+       "131211       131211  TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG   \n",
+       "\n",
+       "             library_label anatomical_division_label  \n",
+       "0       L8TX_180815_01_E08                        TH  \n",
+       "1       L8TX_180829_01_C10                        TH  \n",
+       "2       L8TX_180829_01_B09                        TH  \n",
+       "3       L8TX_180815_01_D08                        TH  \n",
+       "4       L8TX_180815_01_D08                        TH  \n",
+       "...                    ...                       ...  \n",
+       "131207  L8TX_190321_01_G03                        TH  \n",
+       "131208  L8TX_190321_01_G03                        TH  \n",
+       "131209  L8TX_190321_01_H03                        TH  \n",
+       "131210  L8TX_190321_01_H03                        TH  \n",
+       "131211  L8TX_190321_01_H03                        TH  \n",
+       "\n",
+       "[131212 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.obs().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3835</td>\n",
+       "      <td>ENSMUSG00000037771</td>\n",
+       "      <td>Slc32a1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12190</td>\n",
+       "      <td>ENSMUSG00000070570</td>\n",
+       "      <td>Slc17a7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>12316</td>\n",
+       "      <td>ENSMUSG00000039728</td>\n",
+       "      <td>Slc6a5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12321</td>\n",
+       "      <td>ENSMUSG00000030500</td>\n",
+       "      <td>Slc17a6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>14782</td>\n",
+       "      <td>ENSMUSG00000055368</td>\n",
+       "      <td>Slc6a2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>18122</td>\n",
+       "      <td>ENSMUSG00000019935</td>\n",
+       "      <td>Slc17a8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>18521</td>\n",
+       "      <td>ENSMUSG00000025400</td>\n",
+       "      <td>Tac2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>19691</td>\n",
+       "      <td>ENSMUSG00000020838</td>\n",
+       "      <td>Slc6a4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>23107</td>\n",
+       "      <td>ENSMUSG00000021609</td>\n",
+       "      <td>Slc6a3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>23903</td>\n",
+       "      <td>ENSMUSG00000100241</td>\n",
+       "      <td>Slc18a3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   soma_joinid     gene_identifier gene_symbol\n",
+       "0         3835  ENSMUSG00000037771     Slc32a1\n",
+       "1        12190  ENSMUSG00000070570     Slc17a7\n",
+       "2        12316  ENSMUSG00000039728      Slc6a5\n",
+       "3        12321  ENSMUSG00000030500     Slc17a6\n",
+       "4        14782  ENSMUSG00000055368      Slc6a2\n",
+       "5        18122  ENSMUSG00000019935     Slc17a8\n",
+       "6        18521  ENSMUSG00000025400        Tac2\n",
+       "7        19691  ENSMUSG00000020838      Slc6a4\n",
+       "8        23107  ENSMUSG00000021609      Slc6a3\n",
+       "9        23903  ENSMUSG00000100241     Slc18a3"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.var().concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "The query executed successfully and returned a filtered subset of your original TileDB experiment.\n",
+    "\n",
+    "Time taken: The query executed in approximately 0.0002724 seconds, which is very fast.\n",
+    "\n",
+    "Number of variables and observations: Your query returned data for 10 genes (\"variables\") across 131,212 cells (\"observations\"). These counts match your filter criteria, suggesting the query was successful.\n",
+    "\n",
+    "Observation Metadata: The query.obs().concat().to_pandas() output shows the metadata for 131,212 cells. It includes various information like soma_joinid, cell_label, cell_barcode, library_label, and anatomical_division_label. This information is generally used to understand the context or origin of each cell's data.\n",
+    "\n",
+    "Variable Metadata: The query.var().concat().to_pandas() output shows the metadata for the 10 genes you were interested in. It includes the soma_joinid, gene_identifier, and gene_symbol. These identifiers are crucial for tracing back which gene each row of data corresponds to."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   soma_joinid                cell_label      cell_barcode   \n",
+      "0            0  CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA  \\\n",
+      "1            1  TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC   \n",
+      "2            2  CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT   \n",
+      "3            3  GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG   \n",
+      "4            4  GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA   \n",
+      "\n",
+      "        library_label anatomical_division_label  \n",
+      "0  L8TX_180815_01_E08                        TH  \n",
+      "1  L8TX_180829_01_C10                        TH  \n",
+      "2  L8TX_180829_01_B09                        TH  \n",
+      "3  L8TX_180815_01_D08                        TH  \n",
+      "4  L8TX_180815_01_D08                        TH  \n"
+     ]
+    }
+   ],
+   "source": [
+    "print(query.obs().concat().to_pandas().head())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "pyarrow.Table\n",
+       "soma_joinid: int64\n",
+       "cell_label: large_string\n",
+       "anatomical_division_label: large_string\n",
+       "----\n",
+       "soma_joinid: [[0,1,2,3,4,...,131207,131208,131209,131210,131211]]\n",
+       "cell_label: [[\"CAGGTGCAGGCTAGCA-040_C01\",\"TGCGCAGGTTGCGCAC-045_C01\",\"CGATGTATCTTGCCGT-042_B01\",\"GACTAACGTCCTCTTG-040_B01\",\"GATCGTACAACTGCTA-040_B01\",...,\"GTACTCCGTAGTACCT-103_B01\",\"GTGAAGGTCAGCTCTC-103_B01\",\"ACACCCTCATGCGCAC-103_C01\",\"CCTAAAGCAAGAGGCT-103_C01\",\"TCTGGAAAGATGAGAG-103_C01\"]]\n",
+       "anatomical_division_label: [[\"TH\",\"TH\",\"TH\",\"TH\",\"TH\",...,\"TH\",\"TH\",\"TH\",\"TH\",\"TH\"]]"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# you can choose a subset of columns\n",
+    "query.obs(column_names=[\"soma_joinid\", \"cell_label\", \"anatomical_division_label\"]).concat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>cell_label</th>\n",
+       "      <th>anatomical_division_label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>CAGGTGCAGGCTAGCA-040_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>TGCGCAGGTTGCGCAC-045_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>CGATGTATCTTGCCGT-042_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>GACTAACGTCCTCTTG-040_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>GATCGTACAACTGCTA-040_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131207</th>\n",
+       "      <td>131207</td>\n",
+       "      <td>GTACTCCGTAGTACCT-103_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131208</th>\n",
+       "      <td>131208</td>\n",
+       "      <td>GTGAAGGTCAGCTCTC-103_B01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131209</th>\n",
+       "      <td>131209</td>\n",
+       "      <td>ACACCCTCATGCGCAC-103_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131210</th>\n",
+       "      <td>131210</td>\n",
+       "      <td>CCTAAAGCAAGAGGCT-103_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131211</th>\n",
+       "      <td>131211</td>\n",
+       "      <td>TCTGGAAAGATGAGAG-103_C01</td>\n",
+       "      <td>TH</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>131212 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        soma_joinid                cell_label anatomical_division_label\n",
+       "0                 0  CAGGTGCAGGCTAGCA-040_C01                        TH\n",
+       "1                 1  TGCGCAGGTTGCGCAC-045_C01                        TH\n",
+       "2                 2  CGATGTATCTTGCCGT-042_B01                        TH\n",
+       "3                 3  GACTAACGTCCTCTTG-040_B01                        TH\n",
+       "4                 4  GATCGTACAACTGCTA-040_B01                        TH\n",
+       "...             ...                       ...                       ...\n",
+       "131207       131207  GTACTCCGTAGTACCT-103_B01                        TH\n",
+       "131208       131208  GTGAAGGTCAGCTCTC-103_B01                        TH\n",
+       "131209       131209  ACACCCTCATGCGCAC-103_C01                        TH\n",
+       "131210       131210  CCTAAAGCAAGAGGCT-103_C01                        TH\n",
+       "131211       131211  TCTGGAAAGATGAGAG-103_C01                        TH\n",
+       "\n",
+       "[131212 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.obs(column_names=[\"soma_joinid\", \"cell_label\", \"anatomical_division_label\"]).concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<tiledbsoma._sparse_nd_array.SparseNDArrayRead at 0x7f32cce80110>"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query.X(layer_name=\"data\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        soma_dim_0  soma_dim_1  soma_data\n",
+      "0                0        3835   9.105261\n",
+      "1                1        3835   7.724693\n",
+      "2                2        3835   7.578836\n",
+      "3                3        3835   6.765602\n",
+      "4                4        3835   7.625302\n",
+      "...            ...         ...        ...\n",
+      "151421      131195       12321   8.086309\n",
+      "151422      131196       12321   9.037983\n",
+      "151423      131201       12321   9.588039\n",
+      "151424      131202       12321   8.654383\n",
+      "151425      131186       18521   8.314970\n",
+      "\n",
+      "[151426 rows x 3 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Fetch the filtered expression data\n",
+    "filtered_expression_data = query.X(layer_name=\"data\").tables().concat().to_pandas()\n",
+    "print(filtered_expression_data)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " let's unpack what this DataFrame represents:\n",
+    "\n",
+    "soma_dim_0: This column appears to represent the index for the observations (cells), matching the soma_joinid in the observation metadata. Each unique value in this column likely corresponds to a unique cell in your dataset.\n",
+    "\n",
+    "soma_dim_1: This column appears to represent the index for the variables (genes), matching with the soma_joinid in the variable metadata. Each unique value in this column likely corresponds to a unique gene in your dataset.\n",
+    "\n",
+    "soma_data: This column contains the expression values for each gene in each cell.\n",
+    "\n",
+    "How to Interpret the DataFrame\n",
+    "The DataFrame is essentially a long-form representation of the gene expression matrix for the filtered dataset.\n",
+    "\n",
+    "Each row in the DataFrame corresponds to a specific cell-gene pair.\n",
+    "The soma_dim_0 value tells you which cell the data point belongs to.\n",
+    "The soma_dim_1 value tells you which gene the data point corresponds to.\n",
+    "The soma_data value gives you the expression level of that gene in that cell.\n",
+    "For example, the first row tells you that for the cell with index 0 (soma_dim_0), the gene with index 3835 (soma_dim_1) has an expression level of approximately 9.105 (soma_data).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The discrepancy between the number of rows in the expression data DataFrame ([151426 rows x 3 columns]) and the number of rows in the observation data ([131212 rows x 3 columns]) likely arises from the nature of the expression data and how it is stored or filtered.\n",
+    "\n",
+    "Here are some factors that could explain this:\n",
+    "\n",
+    "Sparse Nature of Data:\n",
+    "Gene expression data is often sparse. Not every gene is expressed in every cell, and the data storage might optimize for this by only including entries where the expression level exceeds a certain threshold. If a gene is not expressed in a particular cell, there might be no entry for that cell-gene pair, reducing the total number of rows.\n",
+    "Filtering:\n",
+    "You've filtered the gene set to a specific list of 10 genes (given by filtered_gene_symbols). Therefore, each cell can have at most 10 entries in the expression data, one for each gene. However, if some of these genes are not expressed in some cells, those cells will have fewer than 10 entries, contributing to the reduced number of rows.\n",
+    "Calculating Expected Rows:\n",
+    "If every one of the 10 genes were expressed in each of the 131212 cells, you would expect to see \n",
+    "10\n",
+    "×\n",
+    "131212\n",
+    "=\n",
+    "1312120\n",
+    "10×131212=1312120 rows. However, you only see 151426 rows, which suggests that not all genes are expressed in all cells.\n",
+    "Summary:\n",
+    "The 151426 rows mean there are that many cell-gene pairs where the gene is actually expressed in the cell, given your filtering conditions on which genes to include.\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "The query and asubset objects aim to achieve similar objectives but in different ways and potentially with different types of optimizations.\n",
+    "Similarities:\n",
+    "Data Scope: Both are designed to represent a subset of the original dataset, focusing only on the cells and genes of interest. In your case, you're interested in a specific list of 10 genes.\n",
+    "\n",
+    "Attributes: Both contain information about observations (cells) and variables (genes), albeit in slightly different formats. For instance, asubset is an AnnData object which contains .obs and .var attributes to access cell and gene metadata, respectively. The query object provides similar functionalities through methods like query.obs() and query.var().\n",
+    "\n",
+    "Differences:\n",
+    "Efficiency: query is optimized for efficient querying without necessarily loading the whole data into memory. It allows you to perform various types of queries and fetch only what you need. The asubset.to_memory() explicitly loads the data into memory, which might be less efficient for very large datasets.\n",
+    "\n",
+    "Flexibility: The query object allows more complex querying and slicing capabilities, especially useful when working with large-scale, distributed databases like TileDB.\n",
+    "\n",
+    "Data Structure: asubset is an AnnData object,  query is a more general object tailored for querying TileDB databases.\n",
+    "\n",
+    "Time Taken: Based on your timing data, fetching asubset took around 7 seconds to complete. The query object typically builds the query very quickly but fetches data lazily, meaning the actual data is fetched only when you request it, so the time complexity might differ depending on what you do next with the query.\n",
+    "\n",
+    "In summary, while both are designed to subset the data based on genes of interest, they have different underlying architectures and use-cases. You would use asubset when you're working in-memory and have sufficient resources to do so. You would use query when you want to efficiently query large-scale data without necessarily loading it into memory."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Slicing and Filtering Objects\n",
+    "One of the most useful features of SOMA is the ability to efficiently\n",
+    "filter and select only the data necessary for your analysis without\n",
+    "loading the entire dataset into memory first. The `read` methods offer\n",
+    "several arguments to access a specific subset of data:\n",
+    "\n",
+    "-   `coords` to slice by coordinates from the underlying TileDB array’s\n",
+    "    indexed dimension(s)\n",
+    "-   `value_filter` to filter by values using a query string\n",
+    "-   `column_names` to select the specific columns that should be\n",
+    "    returned\"\n",
+    "    \n",
+    "*Note: the `soma_joinid` represents the indexed dimension of the `obs` array, which contains a unique integer identifier for each record. This is useful for joining with other SOMA objects in the same Experiment.*   \n",
+    "\n",
+    "You can learn more about the `read` methods here: https://tiledbsoma.readthedocs.io/en/latest/notebooks/tutorial_soma_reading.html#"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-09-27 11:44:50.019] [tiledbsoma] [Process: 94727] [Thread: 94727] [warning] [TileDB-SOMA::ManagedQuery] [<DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')> reader] Invalid column selected: cell_label\n",
+      "[2023-09-27 11:44:50.019] [tiledbsoma] [Process: 94727] [Thread: 94727] [warning] [TileDB-SOMA::ManagedQuery] [<DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')> reader] Invalid column selected: library_label\n",
+      "[2023-09-27 11:44:50.019] [tiledbsoma] [Process: 94727] [Thread: 94727] [warning] [TileDB-SOMA::ManagedQuery] [<DataFrame 'file:///shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var' (open for 'r')> reader] Invalid column selected: anatomical_division_label\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>soma_joinid</th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3835</td>\n",
+       "      <td>Slc32a1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12190</td>\n",
+       "      <td>Slc17a7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>12316</td>\n",
+       "      <td>Slc6a5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12321</td>\n",
+       "      <td>Slc17a6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>14782</td>\n",
+       "      <td>Slc6a2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>18122</td>\n",
+       "      <td>Slc17a8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>18521</td>\n",
+       "      <td>Tac2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>19691</td>\n",
+       "      <td>Slc6a4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>23107</td>\n",
+       "      <td>Slc6a3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>23903</td>\n",
+       "      <td>Slc18a3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   soma_joinid gene_symbol\n",
+       "0         3835     Slc32a1\n",
+       "1        12190     Slc17a7\n",
+       "2        12316      Slc6a5\n",
+       "3        12321     Slc17a6\n",
+       "4        14782      Slc6a2\n",
+       "5        18122     Slc17a8\n",
+       "6        18521        Tac2\n",
+       "7        19691      Slc6a4\n",
+       "8        23107      Slc6a3\n",
+       "9        23903     Slc18a3"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tdbs.ms[\"RNA\"].var.read(\n",
+    "    value_filter=\"gene_symbol in ['Slc17a7', 'Slc17a6', 'Slc17a8', 'Slc32a1', 'Slc6a5', 'Slc18a3', 'Slc6a3', 'Slc6a4', 'Slc6a2', 'Tac2']\",\n",
+    "    column_names=[\"soma_joinid\", \"cell_label\", \"library_label\", \"anatomical_division_label\"],\n",
+    ").concat().to_pandas()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We define two helper functions to (1) *create_expression_dataframe*: create joined gene expression and cell metadata dataframe based for a set of input genes and (2) *aggregate_by_metadata* which computes the average expression for each term in a given category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_expression_dataframe( ad, gf ) :\n",
+    "    gdata = ad[:,gf.index].to_df()\n",
+    "    gdata.columns = gf.gene_symbol\n",
+    "    joined = cell_filtered.join( gdata )\n",
+    "    return joined"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def aggregate_by_metadata( df, gnames, value, sort=False ) :\n",
+    "    grouped = df.groupby(value)[gnames].mean()\n",
+    "    if sort :\n",
+    "        grouped = grouped.sort_values(by=gnames[0],ascending=False)\n",
+    "    return grouped"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AnnData object with n_obs × n_vars = 131212 × 10\n",
+       "    obs: 'cell_barcode', 'library_label', 'anatomical_division_label'\n",
+       "    var: 'gene_symbol'\n",
+       "    uns: 'normalization', 'parent', 'parent_layer', 'parent_rows'"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "asubset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th>ENSMUSG00000037771</th>\n",
+       "      <th>ENSMUSG00000070570</th>\n",
+       "      <th>ENSMUSG00000039728</th>\n",
+       "      <th>ENSMUSG00000030500</th>\n",
+       "      <th>ENSMUSG00000055368</th>\n",
+       "      <th>ENSMUSG00000019935</th>\n",
+       "      <th>ENSMUSG00000025400</th>\n",
+       "      <th>ENSMUSG00000020838</th>\n",
+       "      <th>ENSMUSG00000021609</th>\n",
+       "      <th>ENSMUSG00000100241</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cell_label</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>CAGGTGCAGGCTAGCA-040_C01</th>\n",
+       "      <td>9.105261</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TGCGCAGGTTGCGCAC-045_C01</th>\n",
+       "      <td>7.724693</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CGATGTATCTTGCCGT-042_B01</th>\n",
+       "      <td>7.578836</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GACTAACGTCCTCTTG-040_B01</th>\n",
+       "      <td>6.765602</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GATCGTACAACTGCTA-040_B01</th>\n",
+       "      <td>7.625302</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>6.632591</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTACTCCGTAGTACCT-103_B01</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTGAAGGTCAGCTCTC-103_B01</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>10.389612</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ACACCCTCATGCGCAC-103_C01</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CCTAAAGCAAGAGGCT-103_C01</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TCTGGAAAGATGAGAG-103_C01</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>131212 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "gene_identifier           ENSMUSG00000037771  ENSMUSG00000070570   \n",
+       "cell_label                                                         \n",
+       "CAGGTGCAGGCTAGCA-040_C01            9.105261            0.000000  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01            7.724693            0.000000   \n",
+       "CGATGTATCTTGCCGT-042_B01            7.578836            0.000000   \n",
+       "GACTAACGTCCTCTTG-040_B01            6.765602            0.000000   \n",
+       "GATCGTACAACTGCTA-040_B01            7.625302            0.000000   \n",
+       "...                                      ...                 ...   \n",
+       "GTACTCCGTAGTACCT-103_B01            0.000000            0.000000   \n",
+       "GTGAAGGTCAGCTCTC-103_B01            0.000000           10.389612   \n",
+       "ACACCCTCATGCGCAC-103_C01            0.000000            0.000000   \n",
+       "CCTAAAGCAAGAGGCT-103_C01            0.000000            0.000000   \n",
+       "TCTGGAAAGATGAGAG-103_C01            0.000000            0.000000   \n",
+       "\n",
+       "gene_identifier           ENSMUSG00000039728  ENSMUSG00000030500   \n",
+       "cell_label                                                         \n",
+       "CAGGTGCAGGCTAGCA-040_C01                 0.0            0.000000  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                 0.0            0.000000   \n",
+       "CGATGTATCTTGCCGT-042_B01                 0.0            0.000000   \n",
+       "GACTAACGTCCTCTTG-040_B01                 0.0            0.000000   \n",
+       "GATCGTACAACTGCTA-040_B01                 0.0            6.632591   \n",
+       "...                                      ...                 ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                 0.0            0.000000   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                 0.0            0.000000   \n",
+       "ACACCCTCATGCGCAC-103_C01                 0.0            0.000000   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                 0.0            0.000000   \n",
+       "TCTGGAAAGATGAGAG-103_C01                 0.0            0.000000   \n",
+       "\n",
+       "gene_identifier           ENSMUSG00000055368  ENSMUSG00000019935   \n",
+       "cell_label                                                         \n",
+       "CAGGTGCAGGCTAGCA-040_C01                 0.0                 0.0  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                 0.0                 0.0   \n",
+       "CGATGTATCTTGCCGT-042_B01                 0.0                 0.0   \n",
+       "GACTAACGTCCTCTTG-040_B01                 0.0                 0.0   \n",
+       "GATCGTACAACTGCTA-040_B01                 0.0                 0.0   \n",
+       "...                                      ...                 ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                 0.0                 0.0   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                 0.0                 0.0   \n",
+       "ACACCCTCATGCGCAC-103_C01                 0.0                 0.0   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                 0.0                 0.0   \n",
+       "TCTGGAAAGATGAGAG-103_C01                 0.0                 0.0   \n",
+       "\n",
+       "gene_identifier           ENSMUSG00000025400  ENSMUSG00000020838   \n",
+       "cell_label                                                         \n",
+       "CAGGTGCAGGCTAGCA-040_C01                 0.0                 0.0  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                 0.0                 0.0   \n",
+       "CGATGTATCTTGCCGT-042_B01                 0.0                 0.0   \n",
+       "GACTAACGTCCTCTTG-040_B01                 0.0                 0.0   \n",
+       "GATCGTACAACTGCTA-040_B01                 0.0                 0.0   \n",
+       "...                                      ...                 ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                 0.0                 0.0   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                 0.0                 0.0   \n",
+       "ACACCCTCATGCGCAC-103_C01                 0.0                 0.0   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                 0.0                 0.0   \n",
+       "TCTGGAAAGATGAGAG-103_C01                 0.0                 0.0   \n",
+       "\n",
+       "gene_identifier           ENSMUSG00000021609  ENSMUSG00000100241  \n",
+       "cell_label                                                        \n",
+       "CAGGTGCAGGCTAGCA-040_C01                 0.0                 0.0  \n",
+       "TGCGCAGGTTGCGCAC-045_C01                 0.0                 0.0  \n",
+       "CGATGTATCTTGCCGT-042_B01                 0.0                 0.0  \n",
+       "GACTAACGTCCTCTTG-040_B01                 0.0                 0.0  \n",
+       "GATCGTACAACTGCTA-040_B01                 0.0                 0.0  \n",
+       "...                                      ...                 ...  \n",
+       "GTACTCCGTAGTACCT-103_B01                 0.0                 0.0  \n",
+       "GTGAAGGTCAGCTCTC-103_B01                 0.0                 0.0  \n",
+       "ACACCCTCATGCGCAC-103_C01                 0.0                 0.0  \n",
+       "CCTAAAGCAAGAGGCT-103_C01                 0.0                 0.0  \n",
+       "TCTGGAAAGATGAGAG-103_C01                 0.0                 0.0  \n",
+       "\n",
+       "[131212 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "asubset[:,gene_filtered.index].to_df()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gene_identifier           ENSMUSG00000037771  ENSMUSG00000070570   \n",
+      "cell_label                                                         \n",
+      "CAGGTGCAGGCTAGCA-040_C01            9.105261            0.000000  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01            7.724693            0.000000   \n",
+      "CGATGTATCTTGCCGT-042_B01            7.578836            0.000000   \n",
+      "GACTAACGTCCTCTTG-040_B01            6.765602            0.000000   \n",
+      "GATCGTACAACTGCTA-040_B01            7.625302            0.000000   \n",
+      "...                                      ...                 ...   \n",
+      "GTACTCCGTAGTACCT-103_B01            0.000000            0.000000   \n",
+      "GTGAAGGTCAGCTCTC-103_B01            0.000000           10.389612   \n",
+      "ACACCCTCATGCGCAC-103_C01            0.000000            0.000000   \n",
+      "CCTAAAGCAAGAGGCT-103_C01            0.000000            0.000000   \n",
+      "TCTGGAAAGATGAGAG-103_C01            0.000000            0.000000   \n",
+      "\n",
+      "gene_identifier           ENSMUSG00000039728  ENSMUSG00000030500   \n",
+      "cell_label                                                         \n",
+      "CAGGTGCAGGCTAGCA-040_C01                 0.0            0.000000  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01                 0.0            0.000000   \n",
+      "CGATGTATCTTGCCGT-042_B01                 0.0            0.000000   \n",
+      "GACTAACGTCCTCTTG-040_B01                 0.0            0.000000   \n",
+      "GATCGTACAACTGCTA-040_B01                 0.0            6.632591   \n",
+      "...                                      ...                 ...   \n",
+      "GTACTCCGTAGTACCT-103_B01                 0.0            0.000000   \n",
+      "GTGAAGGTCAGCTCTC-103_B01                 0.0            0.000000   \n",
+      "ACACCCTCATGCGCAC-103_C01                 0.0            0.000000   \n",
+      "CCTAAAGCAAGAGGCT-103_C01                 0.0            0.000000   \n",
+      "TCTGGAAAGATGAGAG-103_C01                 0.0            0.000000   \n",
+      "\n",
+      "gene_identifier           ENSMUSG00000055368  ENSMUSG00000019935   \n",
+      "cell_label                                                         \n",
+      "CAGGTGCAGGCTAGCA-040_C01                 0.0                 0.0  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01                 0.0                 0.0   \n",
+      "CGATGTATCTTGCCGT-042_B01                 0.0                 0.0   \n",
+      "GACTAACGTCCTCTTG-040_B01                 0.0                 0.0   \n",
+      "GATCGTACAACTGCTA-040_B01                 0.0                 0.0   \n",
+      "...                                      ...                 ...   \n",
+      "GTACTCCGTAGTACCT-103_B01                 0.0                 0.0   \n",
+      "GTGAAGGTCAGCTCTC-103_B01                 0.0                 0.0   \n",
+      "ACACCCTCATGCGCAC-103_C01                 0.0                 0.0   \n",
+      "CCTAAAGCAAGAGGCT-103_C01                 0.0                 0.0   \n",
+      "TCTGGAAAGATGAGAG-103_C01                 0.0                 0.0   \n",
+      "\n",
+      "gene_identifier           ENSMUSG00000025400  ENSMUSG00000020838   \n",
+      "cell_label                                                         \n",
+      "CAGGTGCAGGCTAGCA-040_C01                 0.0                 0.0  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01                 0.0                 0.0   \n",
+      "CGATGTATCTTGCCGT-042_B01                 0.0                 0.0   \n",
+      "GACTAACGTCCTCTTG-040_B01                 0.0                 0.0   \n",
+      "GATCGTACAACTGCTA-040_B01                 0.0                 0.0   \n",
+      "...                                      ...                 ...   \n",
+      "GTACTCCGTAGTACCT-103_B01                 0.0                 0.0   \n",
+      "GTGAAGGTCAGCTCTC-103_B01                 0.0                 0.0   \n",
+      "ACACCCTCATGCGCAC-103_C01                 0.0                 0.0   \n",
+      "CCTAAAGCAAGAGGCT-103_C01                 0.0                 0.0   \n",
+      "TCTGGAAAGATGAGAG-103_C01                 0.0                 0.0   \n",
+      "\n",
+      "gene_identifier           ENSMUSG00000021609  ENSMUSG00000100241  \n",
+      "cell_label                                                        \n",
+      "CAGGTGCAGGCTAGCA-040_C01                 0.0                 0.0  \n",
+      "TGCGCAGGTTGCGCAC-045_C01                 0.0                 0.0  \n",
+      "CGATGTATCTTGCCGT-042_B01                 0.0                 0.0  \n",
+      "GACTAACGTCCTCTTG-040_B01                 0.0                 0.0  \n",
+      "GATCGTACAACTGCTA-040_B01                 0.0                 0.0  \n",
+      "...                                      ...                 ...  \n",
+      "GTACTCCGTAGTACCT-103_B01                 0.0                 0.0  \n",
+      "GTGAAGGTCAGCTCTC-103_B01                 0.0                 0.0  \n",
+      "ACACCCTCATGCGCAC-103_C01                 0.0                 0.0  \n",
+      "CCTAAAGCAAGAGGCT-103_C01                 0.0                 0.0  \n",
+      "TCTGGAAAGATGAGAG-103_C01                 0.0                 0.0  \n",
+      "\n",
+      "[131212 rows x 10 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "gdata = asubset[:,gene_filtered.index].to_df()\n",
+    "print(gdata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000037771</th>\n",
+       "      <td>Slc32a1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000070570</th>\n",
+       "      <td>Slc17a7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000039728</th>\n",
+       "      <td>Slc6a5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000030500</th>\n",
+       "      <td>Slc17a6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000055368</th>\n",
+       "      <td>Slc6a2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000019935</th>\n",
+       "      <td>Slc17a8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000025400</th>\n",
+       "      <td>Tac2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000020838</th>\n",
+       "      <td>Slc6a4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000021609</th>\n",
+       "      <td>Slc6a3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000100241</th>\n",
+       "      <td>Slc18a3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   gene_symbol\n",
+       "gene_identifier               \n",
+       "ENSMUSG00000037771     Slc32a1\n",
+       "ENSMUSG00000070570     Slc17a7\n",
+       "ENSMUSG00000039728      Slc6a5\n",
+       "ENSMUSG00000030500     Slc17a6\n",
+       "ENSMUSG00000055368      Slc6a2\n",
+       "ENSMUSG00000019935     Slc17a8\n",
+       "ENSMUSG00000025400        Tac2\n",
+       "ENSMUSG00000020838      Slc6a4\n",
+       "ENSMUSG00000021609      Slc6a3\n",
+       "ENSMUSG00000100241     Slc18a3"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gene_filtered"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "gene_identifier\n",
+       "ENSMUSG00000037771    Slc32a1\n",
+       "ENSMUSG00000070570    Slc17a7\n",
+       "ENSMUSG00000039728     Slc6a5\n",
+       "ENSMUSG00000030500    Slc17a6\n",
+       "ENSMUSG00000055368     Slc6a2\n",
+       "ENSMUSG00000019935    Slc17a8\n",
+       "ENSMUSG00000025400       Tac2\n",
+       "ENSMUSG00000020838     Slc6a4\n",
+       "ENSMUSG00000021609     Slc6a3\n",
+       "ENSMUSG00000100241    Slc18a3\n",
+       "Name: gene_symbol, dtype: object"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gene_filtered.gene_symbol"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gene_symbol                Slc32a1    Slc17a7  Slc6a5   Slc17a6  Slc6a2   \n",
+      "cell_label                                                                \n",
+      "CAGGTGCAGGCTAGCA-040_C01  9.105261   0.000000     0.0  0.000000     0.0  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01  7.724693   0.000000     0.0  0.000000     0.0   \n",
+      "CGATGTATCTTGCCGT-042_B01  7.578836   0.000000     0.0  0.000000     0.0   \n",
+      "GACTAACGTCCTCTTG-040_B01  6.765602   0.000000     0.0  0.000000     0.0   \n",
+      "GATCGTACAACTGCTA-040_B01  7.625302   0.000000     0.0  6.632591     0.0   \n",
+      "...                            ...        ...     ...       ...     ...   \n",
+      "GTACTCCGTAGTACCT-103_B01  0.000000   0.000000     0.0  0.000000     0.0   \n",
+      "GTGAAGGTCAGCTCTC-103_B01  0.000000  10.389612     0.0  0.000000     0.0   \n",
+      "ACACCCTCATGCGCAC-103_C01  0.000000   0.000000     0.0  0.000000     0.0   \n",
+      "CCTAAAGCAAGAGGCT-103_C01  0.000000   0.000000     0.0  0.000000     0.0   \n",
+      "TCTGGAAAGATGAGAG-103_C01  0.000000   0.000000     0.0  0.000000     0.0   \n",
+      "\n",
+      "gene_symbol               Slc17a8  Tac2  Slc6a4  Slc6a3  Slc18a3  \n",
+      "cell_label                                                        \n",
+      "CAGGTGCAGGCTAGCA-040_C01      0.0   0.0     0.0     0.0      0.0  \n",
+      "TGCGCAGGTTGCGCAC-045_C01      0.0   0.0     0.0     0.0      0.0  \n",
+      "CGATGTATCTTGCCGT-042_B01      0.0   0.0     0.0     0.0      0.0  \n",
+      "GACTAACGTCCTCTTG-040_B01      0.0   0.0     0.0     0.0      0.0  \n",
+      "GATCGTACAACTGCTA-040_B01      0.0   0.0     0.0     0.0      0.0  \n",
+      "...                           ...   ...     ...     ...      ...  \n",
+      "GTACTCCGTAGTACCT-103_B01      0.0   0.0     0.0     0.0      0.0  \n",
+      "GTGAAGGTCAGCTCTC-103_B01      0.0   0.0     0.0     0.0      0.0  \n",
+      "ACACCCTCATGCGCAC-103_C01      0.0   0.0     0.0     0.0      0.0  \n",
+      "CCTAAAGCAAGAGGCT-103_C01      0.0   0.0     0.0     0.0      0.0  \n",
+      "TCTGGAAAGATGAGAG-103_C01      0.0   0.0     0.0     0.0      0.0  \n",
+      "\n",
+      "[131212 rows x 10 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "gdata.columns = gene_filtered.gene_symbol\n",
+    "print(gdata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                              cell_barcode barcoded_cell_sample_label   \n",
+      "cell_label                                                              \n",
+      "CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA                    040_C01  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC                    045_C01   \n",
+      "CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT                    042_B01   \n",
+      "GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG                    040_B01   \n",
+      "GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA                    040_B01   \n",
+      "...                                    ...                        ...   \n",
+      "GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT                    103_B01   \n",
+      "GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC                    103_B01   \n",
+      "ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC                    103_C01   \n",
+      "CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT                    103_C01   \n",
+      "TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG                    103_C01   \n",
+      "\n",
+      "                               library_label feature_matrix_label entity   \n",
+      "cell_label                                                                 \n",
+      "CAGGTGCAGGCTAGCA-040_C01  L8TX_180815_01_E08         WMB-10Xv2-TH   cell  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01  L8TX_180829_01_C10         WMB-10Xv2-TH   cell   \n",
+      "CGATGTATCTTGCCGT-042_B01  L8TX_180829_01_B09         WMB-10Xv2-TH   cell   \n",
+      "GACTAACGTCCTCTTG-040_B01  L8TX_180815_01_D08         WMB-10Xv2-TH   cell   \n",
+      "GATCGTACAACTGCTA-040_B01  L8TX_180815_01_D08         WMB-10Xv2-TH   cell   \n",
+      "...                                      ...                  ...    ...   \n",
+      "GTACTCCGTAGTACCT-103_B01  L8TX_190321_01_G03         WMB-10Xv2-TH   cell   \n",
+      "GTGAAGGTCAGCTCTC-103_B01  L8TX_190321_01_G03         WMB-10Xv2-TH   cell   \n",
+      "ACACCCTCATGCGCAC-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+      "CCTAAAGCAAGAGGCT-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+      "TCTGGAAAGATGAGAG-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+      "\n",
+      "                          brain_section_label library_method   \n",
+      "cell_label                                                     \n",
+      "CAGGTGCAGGCTAGCA-040_C01                  NaN          10Xv2  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01                  NaN          10Xv2   \n",
+      "CGATGTATCTTGCCGT-042_B01                  NaN          10Xv2   \n",
+      "GACTAACGTCCTCTTG-040_B01                  NaN          10Xv2   \n",
+      "GATCGTACAACTGCTA-040_B01                  NaN          10Xv2   \n",
+      "...                                       ...            ...   \n",
+      "GTACTCCGTAGTACCT-103_B01                  NaN          10Xv2   \n",
+      "GTGAAGGTCAGCTCTC-103_B01                  NaN          10Xv2   \n",
+      "ACACCCTCATGCGCAC-103_C01                  NaN          10Xv2   \n",
+      "CCTAAAGCAAGAGGCT-103_C01                  NaN          10Xv2   \n",
+      "TCTGGAAAGATGAGAG-103_C01                  NaN          10Xv2   \n",
+      "\n",
+      "                         region_of_interest_acronym   \n",
+      "cell_label                                            \n",
+      "CAGGTGCAGGCTAGCA-040_C01                         TH  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01                         TH   \n",
+      "CGATGTATCTTGCCGT-042_B01                         TH   \n",
+      "GACTAACGTCCTCTTG-040_B01                         TH   \n",
+      "GATCGTACAACTGCTA-040_B01                         TH   \n",
+      "...                                             ...   \n",
+      "GTACTCCGTAGTACCT-103_B01                         TH   \n",
+      "GTGAAGGTCAGCTCTC-103_B01                         TH   \n",
+      "ACACCCTCATGCGCAC-103_C01                         TH   \n",
+      "CCTAAAGCAAGAGGCT-103_C01                         TH   \n",
+      "TCTGGAAAGATGAGAG-103_C01                         TH   \n",
+      "\n",
+      "                                           donor_label   \n",
+      "cell_label                                               \n",
+      "CAGGTGCAGGCTAGCA-040_C01  Snap25-IRES2-Cre;Ai14-404124  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01  Snap25-IRES2-Cre;Ai14-407905   \n",
+      "CGATGTATCTTGCCGT-042_B01  Snap25-IRES2-Cre;Ai14-407901   \n",
+      "GACTAACGTCCTCTTG-040_B01  Snap25-IRES2-Cre;Ai14-404124   \n",
+      "GATCGTACAACTGCTA-040_B01  Snap25-IRES2-Cre;Ai14-404124   \n",
+      "...                                                ...   \n",
+      "GTACTCCGTAGTACCT-103_B01  Snap25-IRES2-Cre;Ai14-449635   \n",
+      "GTGAAGGTCAGCTCTC-103_B01  Snap25-IRES2-Cre;Ai14-449635   \n",
+      "ACACCCTCATGCGCAC-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+      "CCTAAAGCAAGAGGCT-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+      "TCTGGAAAGATGAGAG-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+      "\n",
+      "                                                donor_genotype  ...   Slc32a1   \n",
+      "cell_label                                                      ...             \n",
+      "CAGGTGCAGGCTAGCA-040_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  9.105261  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  7.724693   \n",
+      "CGATGTATCTTGCCGT-042_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  7.578836   \n",
+      "GACTAACGTCCTCTTG-040_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  6.765602   \n",
+      "GATCGTACAACTGCTA-040_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  7.625302   \n",
+      "...                                                        ...  ...       ...   \n",
+      "GTACTCCGTAGTACCT-103_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  0.000000   \n",
+      "GTGAAGGTCAGCTCTC-103_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  0.000000   \n",
+      "ACACCCTCATGCGCAC-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  0.000000   \n",
+      "CCTAAAGCAAGAGGCT-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  0.000000   \n",
+      "TCTGGAAAGATGAGAG-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  0.000000   \n",
+      "\n",
+      "                            Slc17a7  Slc6a5   Slc17a6  Slc6a2 Slc17a8 Tac2   \n",
+      "cell_label                                                                   \n",
+      "CAGGTGCAGGCTAGCA-040_C01   0.000000     0.0  0.000000     0.0     0.0  0.0  \\\n",
+      "TGCGCAGGTTGCGCAC-045_C01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "CGATGTATCTTGCCGT-042_B01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "GACTAACGTCCTCTTG-040_B01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "GATCGTACAACTGCTA-040_B01   0.000000     0.0  6.632591     0.0     0.0  0.0   \n",
+      "...                             ...     ...       ...     ...     ...  ...   \n",
+      "GTACTCCGTAGTACCT-103_B01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "GTGAAGGTCAGCTCTC-103_B01  10.389612     0.0  0.000000     0.0     0.0  0.0   \n",
+      "ACACCCTCATGCGCAC-103_C01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "CCTAAAGCAAGAGGCT-103_C01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "TCTGGAAAGATGAGAG-103_C01   0.000000     0.0  0.000000     0.0     0.0  0.0   \n",
+      "\n",
+      "                         Slc6a4 Slc6a3 Slc18a3  \n",
+      "cell_label                                      \n",
+      "CAGGTGCAGGCTAGCA-040_C01    0.0    0.0     0.0  \n",
+      "TGCGCAGGTTGCGCAC-045_C01    0.0    0.0     0.0  \n",
+      "CGATGTATCTTGCCGT-042_B01    0.0    0.0     0.0  \n",
+      "GACTAACGTCCTCTTG-040_B01    0.0    0.0     0.0  \n",
+      "GATCGTACAACTGCTA-040_B01    0.0    0.0     0.0  \n",
+      "...                         ...    ...     ...  \n",
+      "GTACTCCGTAGTACCT-103_B01    0.0    0.0     0.0  \n",
+      "GTGAAGGTCAGCTCTC-103_B01    0.0    0.0     0.0  \n",
+      "ACACCCTCATGCGCAC-103_C01    0.0    0.0     0.0  \n",
+      "CCTAAAGCAAGAGGCT-103_C01    0.0    0.0     0.0  \n",
+      "TCTGGAAAGATGAGAG-103_C01    0.0    0.0     0.0  \n",
+      "\n",
+      "[130555 rows x 37 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "joined = cell_filtered.join( gdata )\n",
+    "print(joined)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Expression of canonical neurotransmitter transporter genes in the thalamus\n",
+    "\n",
+    "During analysis, clusters were assigned neurotransmitter identities based on the expression of of canonical neurotransmitter transporter genes. In this example, we create a dataframe comprising of cells in the 'WMB-10Xv2-TH' package and expression of the 9 solute carrier family genes. We then group the cells by the assigned neurotransmitter class and compute the mean expression for each group. We define a helper function that display a dataframe as a heatmap for visualization."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_heatmap( df, fig_width = 8, fig_height = 4, cmap=plt.cm.magma_r, vmax=None) :\n",
+    "\n",
+    "    arr = df.to_numpy()\n",
+    "\n",
+    "    fig, ax = plt.subplots()\n",
+    "    fig.set_size_inches(fig_width,fig_height)\n",
+    "\n",
+    "    res = ax.imshow(arr, cmap = cmap, aspect='auto', vmax=vmax)\n",
+    "    xlabs = df.columns.values\n",
+    "    ylabs = df.index.values\n",
+    "\n",
+    "    ax.set_xticks(range(len(xlabs)))\n",
+    "    ax.set_xticklabels( xlabs )\n",
+    "\n",
+    "    ax.set_yticks(range(len(ylabs)))\n",
+    "    res = ax.set_yticklabels( ylabs )\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Within the thalamus, Slc17a7 is most enriched in cholinergic assigned cells with some expression in glutamatergic types. Genes Slc17a6 is enriched in glutamatergic, Slc32a1 in GABAergic, Slc6a5 in glycinergic, Slc18a3 in cholinergic and Slc6a3 in dopaminergic types, matching the expectation described in the manuscript."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AnnData object with n_obs × n_vars = 131212 × 10\n",
+       "    obs: 'cell_barcode', 'library_label', 'anatomical_division_label'\n",
+       "    var: 'gene_symbol'\n",
+       "    uns: 'normalization', 'parent', 'parent_layer', 'parent_rows'"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "asubset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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KyclR27ZtK3wdHx8fnTp1StL567aXLl2qd955R/Hx8a42JSUluummm5SRkaH+/fvX0AgBAABQG9TaQC1Jc+fOVWJiohISEjR16lR17NhRdrtdW7ZsUU5Ojrp27Sqn06nu3burV69eZY7v1q2bnE6n677UxhgdOnRIknTq1CmtWrVKn3zyif76179Kkt58801FREQoJSXF7QuPkpScnCyn00mgBgAAuMbU6kAdExPjutY5LS1NBw4ckMPhUPv27TVx4kTdf//9io6Odn058eeGDh2qWbNmacaMGZLOf3mxadOmks5fotGyZUtNmzbNdXx6erqGDBlSJkxf6Ot3v/udjhw5ooYNG16hEQMAAMDb2IwxxtNFXIsKCgoUHh6uYY0ek7+da6svmLe9o6dL8DqmQYSnS/AqPps3e7oEr1PSvbunSwCAOqmgoEgRDQYqPz9fYWFhFbarc3f5AAAAAK4mAjUAAABgAYEaAAAAsIBADQAAAFhAoAYAAAAsIFADAAAAFhCoAQAAAAsI1AAAAIAFBGoAAADAglr9p8frgqZBdjnsPp4uw3v4ckr+XO4d73i6BK/SakKkp0sAUFecPePpCryPn7+nK6iVWKEGAAAALCBQAwAAABYQqAEAAAALCNQAAACABQRqAAAAwAICNQAAAGABgRoAAACwgEANAAAAWECgBgAAACwgUAMAAAAWEKgBAAAACwjU/2vq1Km68cYbPV0GAAAAapnLCtSHDh3ShAkTFBsbq4CAADVp0kSJiYl69dVXdfLkSbe2M2fOlI+Pj5577rky/cyfP182m821hYSEqGvXrvrggw/Kfd1FixbJx8dH48ePr1a977//vm699VbVr19fgYGBiouL06hRo5SVlVWtfgAAAICfq3ag3rt3rzp37qyMjAzNmDFDWVlZ2rhxoyZNmqSPP/5Yn376qVv79PR0TZo0Senp6eX2FxYWpry8POXl5SkrK0v9+vVTSkqKdu7cWaat0+nUpEmTtGjRIp0+fbpK9T722GMaNmyYbrzxRi1btkw7d+7UwoULFR0drbS0tOoOHwAAAHBT7UA9btw4+fr6KjMzUykpKWrXrp2io6M1ePBgLV++XIMGDXK1Xbt2rU6dOqVp06apoKBAGzZsKNOfzWZTZGSkIiMj1bp1a02fPl12u13btm1za7dv3z5t2LBBkydPVps2bSpcxb7Ypk2b9Oyzz+r555/X888/r5tvvlktWrRQ165d9cQTT2jFihXlHvf555/Lz89Phw4dctv/0EMP6eabb3Y9Xr9+vW655RYFBQWpfv366tevn44fP15pXQAAAKg7qhWojx49qoyMDI0fP17BwcHltrHZbK5/O51OjRgxQn5+fhoxYoScTucl+y8pKdEbb7whSerSpYvbc/PmzdOAAQMUHh6u1NTUSvuSzl8iEhISonHjxlVa68V69eql6Ohovfnmm659Z8+e1dtvv61Ro0ZJkrKzs3Xbbbepffv22rhxo9atW6dBgwappKSk3D6Li4tVUFDgtgEAAKD2q1ag3rNnj4wxiouLc9vfsGFDhYSEKCQkRI899pgkqaCgQO+9955SU1MlSampqVqyZIkKCwvdjs3Pz3cd6+/vr7Fjx+r1119XTEyMq01paanmz5/v6mv48OFat26d9u3bd8l6d+3apejoaPn6+rr2Pf/8867XCwkJUX5+frnHjh49WvPmzXM9/uijj3T69GmlpKRIkp599lklJCRo7ty56tSpk+Lj4/WnP/1JDRs2LLe/mTNnKjw83LVFRUVdsnYAAADUDjVyl4/NmzcrOztb8fHxKi4ulnR+dTgmJkadOnWSJN14441q2bKlFi9e7HZsaGiosrOzlZ2draysLM2YMUNjxozRRx995GqzatUqFRUVKTk5WdL5AJ+UlOS6Lvv//b//5xaS33777QprHTVqlLKzs/Xaa6+pqKhIxphy240cOVJ79uzRpk2bJJ3/AmVKSoprZf7CCnVVpaWlKT8/37Xl5uZW+VgAAAB4L9/Km/yf2NhY2Wy2Ml8YjI6OliQFBga69jmdTn399dduq8OlpaVKT0/X6NGjXfvsdrtiY2Ndjzt27KiMjAw988wzruuxnU6njh075tZ/aWmptm3bpieffFIJCQnKzs52PdekSRNJUuvWrbVu3TqdPXtWfn5+kqR69eqpXr16OnDgwCXH2rhxYw0aNEjz5s3T9ddfrxUrVmjNmjWu5y+upSocDoccDke1jgEAAID3q9YKdUREhJKSkjRnzhwVFRVV2G779u3KzMzUmjVrXKvP2dnZWrNmjTZu3KicnJxLvo6Pj49OnTol6fx120uXLtU777zj1ldWVpaOHz+ujIwMBQYGKjY21rWFhoZKkkaMGKHCwkLNnTu3OsN0ue+++7R48WLXJSiJiYmu5zp27KjVq1dfVr8AAACoO6q1Qi1Jc+fOVWJiohISEjR16lR17NhRdrtdW7ZsUU5Ojrp27Sqn06nu3burV69eZY7v1q2bnE6n677UxhjX3TROnTqlVatW6ZNPPtFf//pXSdKbb76piIgIpaSklPkSYXJyspxOp/r3719urT169NAjjzyiRx55RP/5z3/0m9/8RlFRUcrLy5PT6ZTNZpPdXvFnin79+iksLEzTp0/XtGnT3J5LS0tThw4dNG7cOI0ZM0b+/v767LPP9Nvf/rbC66gBAABQ91T7GuqYmBhlZWWpb9++SktLU6dOnZSQkKCXX35ZEydO1JQpU/TWW29p6NCh5R4/dOhQLViwQGfPnpV0/suLTZs2VdOmTdWuXTvNmjVL06ZN01/+8hdJ5+9jPWTIkHLvyDF06FAtW7ZMR44cqbDev/3tb1q4cKGysrI0cOBAtW7dWr/97W9VWlqqjRs3KiwsrMJj7Xa7Ro4cqZKSEt1zzz1uz7Vp00YZGRnaunWrunfvrh49emjp0qVul7gAAACg7rOZir6VB0nn7/bx448/atmyZTXab0FBgcLDw/VQyzQ57AE12ndt9vSXnTxdgtf5LrX8+6Vfq1pNiPR0CV6n5LZbPF0CUDudPePpCryPn7+nK/AqBQVFimgwUPn5+ZdchGU5tQL5+fnavn27Fi5cWONhGgAAAHUHgboCgwcP1ubNmzVmzBglJSV5uhwAAAB4KQJ1BS6+RR4AAABQkRr5wy4AAADAtYpADQAAAFhAoAYAAAAsIFADAAAAFhCoAQAAAAsI1AAAAIAF3DbPw/4r8xcKCwv2dBle48QfFni6BK8TtWyUp0vwKo3rT/J0CV4n7/gtni7B69hOnfR0CV7HBAZ5ugTvw18FRA1hhRoAAACwgEANAAAAWECgBgAAACwgUAMAAAAWEKgBAAAACwjUAAAAgAUEagAAAMACAjUAAABgAYEaAAAAsIBADQAAAFhAoAYAAAAsIFD/jM1m04cffujpMgAAAFBLXFOB+tChQ5owYYJiY2MVEBCgJk2aKDExUa+++qpOnjx5WX3Onz9f9erVq9lCAQAAUGv4erqAq2Xv3r1KTExUvXr1NGPGDHXo0EEOh0Pbt2/X66+/rmbNmumOO+7wdJkAAACoZa6ZQD1u3Dj5+voqMzNTwcHBrv3R0dEaPHiwjDFljlmzZo369Omj48ePu1ahs7Oz1blzZ+3bt0/79+/X73//e0nnLxWRpClTpmjq1KlXfDwAAADwDtdEoD569KgyMjI0Y8YMtzB9sQuBuDp69uyp2bNn669//at27twpSQoJCSm3bXFxsYqLi12PCwoKqv16AAAA8D7XxDXUe/bskTFGcXFxbvsbNmyokJAQhYSE6LHHHqt2v/7+/goPD5fNZlNkZKQiIyMrDNQzZ85UeHi4a4uKirqssQAAAMC7XBOBuiKbN29Wdna24uPj3VaPr4S0tDTl5+e7ttzc3Cv6egAAALg6rolLPmJjY2Wz2VyXZVwQHR0tSQoMDCz3OLv9/OeNi6+vPnv27GXV4HA45HA4LutYAAAAeK9rYoU6IiJCSUlJmjNnjoqKiqp8XKNGjSRJeXl5rn3Z2dlubfz9/VVSUlIjdQIAAKD2uSYCtSTNnTtX586dU0JCghYvXqwdO3Zo586deuutt5STkyMfH58yx8TGxioqKkpTp07V7t27tXz5cs2aNcutTatWrVRYWKjVq1fryJEjl30/awAAANRO10ygjomJUVZWlvr27au0tDR16tRJCQkJevnllzVx4kQ99dRTZY7x8/PTokWLlJOTo44dO+qZZ57R9OnT3dr07NlTY8aM0bBhw9SoUSM9++yzV2tIAAAA8AI2U94NmHHFFRQUKDw8XEd//FBhYeXfyu9aVPiHBZ4uweuEpI/ydAlepWn9SZ4uwevkHeeD/M/ZTvHbwp8zgUGeLgGodQoKihTRYKDy8/MVFhZWYbtrZoUaAAAAuBII1AAAAIAFBGoAAADAAgI1AAAAYAGBGgAAALCAQA0AAABYQKAGAAAALCBQAwAAABYQqAEAAAALfD1dwLXu5EML5evv7+kyvEZI+mhPlwAv18M3ydMloBbgrwICuJpYoQYAAAAsIFADAAAAFhCoAQAAAAsI1AAAAIAFBGoAAADAAgI1AAAAYAGBGgAAALCAQA0AAABYQKAGAAAALCBQAwAAABYQqAEAAAALrmigttls+vDDD6/kSwAAAAAeddmB+tChQ5owYYJiY2MVEBCgJk2aKDExUa+++qpOnjx5WX3Onz9f9erVq3L7M2fO6LnnnlOXLl0UHBys8PBwderUSU888YQOHjxYpv3GjRvl4+OjAQMGlHlu//79stlsrs3f31+xsbGaPn26jDFl2h84cED+/v664YYbqjVGAAAA1C2XFaj37t2rzp07KyMjQzNmzFBWVpY2btyoSZMm6eOPP9ann35a03WWUVxcrKSkJM2YMUMjR47U559/ru3bt+ull17SkSNH9PLLL5c5xul06oEHHtDnn39ebuCWpE8//VR5eXnavXu3nnzyST399NNKT08v027+/PlKSUlRQUGBvvjiixofHwAAAGoH38s5aNy4cfL19VVmZqaCg4Nd+6OjozV48OByV3TXrFmjPn366Pjx465V6OzsbHXu3Fn79u3T/v379fvf/17S+UtFJGnKlCmaOnVquTW88MILWrdunTIzM9W5c2fX/hYtWqh3795laigsLNTixYuVmZmpQ4cOaf78+Xr88cfL9BsREaHIyEhJUsuWLTVv3jx99dVXGj16tKuNMUbz5s3T3Llz1bx5czmdTv3iF7+owswBAACgrqn2CvXRo0eVkZGh8ePHu4Xpi10IxNXRs2dPzZ49W2FhYcrLy1NeXp4mTpxYYftFixYpKSnJLUxfqoYlS5aobdu2iouLU2pqqtLT08sN/hfLzMzUl19+WSYsf/bZZzp58qT69u2r1NRUvfPOOyoqKrpkX8XFxSooKHDbAAAAUPtVO1Dv2bNHxhjFxcW57W/YsKFCQkIUEhKixx57rNqF+Pv7Kzw8XDabTZGRkYqMjFRISEiF7Xft2lWmhiFDhrhq6Nmzp9tzTqdTqampkqT+/fsrPz9fa9euLdNvz549FRISIn9/f3Xr1k0pKSm65557yvQ1fPhw+fj46IYbblB0dLTefffdS45v5syZCg8Pd21RUVGXbA8AAIDaocbu8rF582ZlZ2crPj5excXFNdWtZsyY4QrJISEh+u677ypsO3fuXGVnZ2vUqFFuX4zcuXOnNm/erBEjRkiSfH19NWzYMDmdzjJ9LF68WNnZ2dq6dauWLFmipUuXavLkya7nf/rpJ33wwQeucC5Jqamp5fZ1sbS0NOXn57u23NzcKs8BAAAAvFe1r6GOjY2VzWbTzp073fZHR0dLkgIDA8s9zm4/n90vvszi7Nmzlb7emDFjlJKS4np83XXXSZJat25dpoamTZtKkho0aOC23+l06ty5c65jL9ThcDg0Z84chYeHu/ZHRUUpNjZWktSuXTt9++23+q//+i9NnTpVAQEBWrhwoU6fPu12GYgxRqWlpdq1a5fatGlT7jgcDoccDkel4wUAAEDtUu0V6oiICCUlJWnOnDmVXjd8sUaNGkmS8vLyXPuys7Pd2vj7+6ukpMRtX4MGDRQbG+vafH3PfwYYMWKEVq1apaysrEu+7rlz57RgwQLNmjVL2dnZrm3r1q267rrrtGjRokse7+Pjo3PnzunMmTOSzofzRx55pExfN998c7l3AwEAAEDddlmXfMydO1fnzp1TQkKCFi9erB07dmjnzp166623lJOTIx8fnzLHxMbGKioqSlOnTtXu3bu1fPlyzZo1y61Nq1atVFhYqNWrV+vIkSOXvJ/1n//8Z/Xo0UO33XabXnzxRX311Vfat2+fPvnkE61YscJVw8cff6zjx49r9OjRuuGGG9y2oUOHlrlU4+jRozp06JAOHDigFStW6MUXX1SfPn0UFham7OxsffXVV7rvvvvK9DVixAi98cYbOnfu3OVMKQAAAGqpywrUMTExysrKUt++fZWWlqZOnTopISFBL7/8siZOnKinnnqqzDF+fn5atGiRcnJy1LFjRz3zzDOaPn26W5uePXtqzJgxGjZsmBo1aqRnn322whoCAgK0evVqPfbYY5o3b55uuukmtWvXTg899JASExNdf6HR6XSqb9++bpd1XDB06FBlZmZq27Ztrn19+/ZV06ZN1apVK91///1KTk7W4sWLXX21b99ebdu2LdPXkCFDdPjwYf3zn/+s0hwCAACgbrCZyu4dhyuioKBA4eHhyr07RWH+/p4ux2sE/c/oyhvhmvabRqs8XYLX+eDHJE+XAAB1UkFBkSIaDFR+fr7CwsIqbFdjd/kAAAAArkUEagAAAMACAjUAAABgAYEaAAAAsIBADQAAAFhAoAYAAAAsIFADAAAAFhCoAQAAAAt8PV3AterC39M5cfashyvxLucKijxdArzcWVPs6RK8TgHvGwC4IgoKTkr6v9xWEf5SooccOHBAUVFRni4DAAAAlcjNzVXz5s0rfJ5A7SGlpaU6ePCgQkNDZbPZPFZHQUGBoqKilJube8k/qXktYU7KYk7KYk7KYk7KYk7KYk7cMR9ledOcGGN04sQJXXfddbLbK75Smks+PMRut1/yk87VFhYW5vGT1tswJ2UxJ2UxJ2UxJ2UxJ2UxJ+6Yj7K8ZU7Cw8MrbcOXEgEAAAALCNQAAACABQTqa5zD4dCUKVPkcDg8XYrXYE7KYk7KYk7KYk7KYk7KYk7cMR9l1cY54UuJAAAAgAWsUAMAAAAWEKgBAAAACwjUAAAAgAUEagAAAMACAnUtZrPZ9OGHH3q6DK/CnFTNtT5P1/r4q4I5Yg6qgjkq61qfk2t1/ARqL/bjjz9q7NixatGihRwOhyIjI9WvXz+tX7++2n2tW7dOiYmJioiIUGBgoNq2basXXnjBrc3MmTPVrVs3hYaGqnHjxvr1r3+tnTt3Vut1Tp8+rZEjR6pDhw7y9fXVr3/962rXeik1OSd5eXm666671KZNG9ntdj300ENl2txyyy2y2WxltgEDBlT5debPn19uHzabTYcPH6523VVRk/MkScXFxfrLX/6ili1byuFwqFWrVkpPT69WH+XN5ZgxYy6rnsrUxvPkgvnz56tjx44KCAhQ48aNNX78+Gr3URXedo4cO3ZMDzzwgOLi4hQYGKgWLVrowQcfVH5+/mXVUxW19TzZsmWLbrvtNtWrV0/169dXv379tHXr1mrXXBXedp5czBijX/3qV1c9wHnjnPzxj39UTEyMAgMD1ahRIw0ePFg5OTmXVU9lrvb7RpJmz57t+tkQFRWlP//5zzp9+nS1XuuOO+5QixYtFBAQoKZNm+p3v/udDh48WO2aK8KfHvdiQ4cO1ZkzZ/TGG28oOjpaP/zwg1avXq2jR49Wu6/g4GD96U9/UseOHRUcHKx169bpj3/8o4KDg3X//fdLktauXavx48erW7duOnfunB5//HHdfvvt+uabbxQcHFyl1ykpKVFgYKAefPBBvf/++9WuszI1OSfFxcVq1KiRnnjiiTIfLi744IMPdObMGdfjo0ePqlOnTvrtb39b5dcZNmyY+vfv77Zv5MiROn36tBo3blztuquiJudJklJSUvTDDz/I6XQqNjZWeXl5Ki0trXY/f/jDHzRt2jTX46CgoMuqpzK18TyRpOeff16zZs3Sc889p1/84hcqKirS/v37q11zVXjbOXLw4EEdPHhQf/vb39S+fXv95z//0ZgxY3Tw4EG99957l1VTZWrjeVJYWKj+/fvrjjvu0Ny5c3Xu3DlNmTJF/fr1U25urvz8/Kpd+6V423lysdmzZ8tms13WsVZ445x07dpVd999t1q0aKFjx45p6tSpuv3227Vv3z75+PhcVl0Vudrvm4ULF2ry5MlKT09Xz549tWvXLo0cOVI2m03PP/98lV+rT58+evzxx9W0aVN9//33mjhxou68805t2LCh2nWXy8ArHT9+3Egya9asqbCNJPOPf/zD9Tg3N9cMHz7c1K9f3wQFBZmuXbuaTZs2VXj8kCFDTGpqaoXPHz582Egya9eude2bNWuWueGGG0xQUJBp3ry5GTt2rDlx4kS5x997771m8ODBFQ+ymq7knPTu3dtMmDCh0hpeeOEFExoaagoLC137FixYYLp27WpCQkJMkyZNzIgRI8wPP/xQYR+HDx82fn5+ZsGCBZW+3uWo6XlasWKFCQ8PN0ePHq2wv82bN5u+ffuaiIgIExYWZnr16mW+/PJLtzZVnWOraut5cuzYMRMYGGg+/fTTqg3UAm89R35uyZIlxt/f35w9e7Z6A6yC2nqebNmyxUgy3333nWvftm3bjCSze/fuSl+zOrz5PMnKyjLNmjUzeXl5ZWq4krx5Ti62detWI8ns2bOnegOshCfeN+PHjze33nqr276HH37YJCYmuh6vWLHCJCYmmvDwcNOgQQMzYMCASse+dOlSY7PZzJkzZy7Zrqq45MNLhYSEKCQkRB9++KGKi4srbV9YWKjevXvr+++/17Jly7R161ZNmjSpwk+5WVlZ2rBhg3r37l1hnxd+1dqgQQPXPrvdrpdeeklff/213njjDf3rX//SpEmTqjm6y3Ol56QqnE6nhg8f7rZif/bsWT311FPaunWrPvzwQ+3fv18jR46ssI8FCxYoKChId95552XXcSk1PU/Lli1TQkKCnn32WTVr1kxt2rTRxIkTderUKVcfJ06c0L333qt169Zp06ZNat26tZKTk3XixAm313r77bfVsGFD3XDDDUpLS9PJkydrdvCqvefJqlWrVFpaqu+//17t2rVT8+bNlZKSotzc3MuuoyLefI5cLD8/X2FhYfL1rflfptbW8yQuLk4RERFyOp06c+aMTp06JafTqXbt2qlVq1aXXUt5vPU8OXnypO666y698sorioyMrNExV8Zb5+RiRUVFmjdvnq6//npFRUXVzMD/lyfeNz179tSXX36pzZs3S5L27t2rf/7zn0pOTna1KSoq0sMPP6zMzEytXr1adrtdQ4YMqfB1jh07prfffls9e/asud/q1EgsxxXx3nvvmfr165uAgADTs2dPk5aWZrZu3ep6Xhd9CnzttddMaGjoJT/lGmNMs2bNjL+/v7Hb7WbatGkVtispKTEDBgxw+wRYnnfffddERESU+1xNr1Abc2XmxJiqrSh98cUXRpL54osvLtnuwgpSRSv37dq1M2PHjq20Jitqcp769etnHA6HGTBggPniiy/M8uXLTcuWLc3IkSMrfP2SkhITGhpqPvroI9e+1157zaxcudJs27bNvPXWW6ZZs2ZmyJAhNTPgn6mN58nMmTONn5+fiYuLMytXrjQbN240t912m4mLizPFxcWV1lZd3niOXOzHH380LVq0MI8//vjlD7IStfE8McaY7du3m5iYGGO3243dbjdxcXFm//79ldZ1ObzxPLn//vvN6NGjy63havDGOTHGmFdeecUEBwcbSSYuLq7GV6cv8MT75sUXXzR+fn7G19fXSDJjxoy5ZF8//vijkWS2b9/utn/SpEkmKCjISDK//OUvzZEjRyqtq6oI1F7u1KlTJiMjw0ybNs306NHD+Pj4mHnz5hlj3E/asWPHml69elXa3969e822bdvM66+/bho0aGAWLlxYbrsxY8aYli1bmtzcXLf9q1atMrfeequ57rrrTEhIiAkICDCSTFFRUZk+rkSgNqbm58SYqv0HeP/995sOHTqU2Z+ZmWkGDhxooqKiTEhIiOvN+vXXX5dpu2HDBiPJZGZmVqkuK2pqnpKSkkxAQID56aefXPvef/99Y7PZzMmTJ40xxhw6dMjcd999JjY21oSFhZng4GBjs9nMK6+8UmG/q1evviK/krygtp0nTz/9tJFkPvnkE9cxhw8fNna73axcubJK9VWXt54j+fn5pnv37qZ///419uvYitS28+TkyZOme/fu5p577jGbN282GzduNEOHDjXx8fGuua5p3nSeLF261MTGxrp9wLjagdoY75qTC3766Seza9cus3btWjNo0CDTpUsXc+rUqZod+P+6mu+bzz77zDRp0sT8z//8j9m2bZv54IMPTFRUlNui4K5du8zw4cPN9ddfb0JDQ10fLJYvX+7W148//mh27txpMjIyTGJioklOTjalpaWXNQc/R6CuZUaPHm1atGhhjHE/aR9++OEqn7QXPPXUU6ZNmzZl9o8fP940b97c7N27123/vn37jMPhMA899JDZuHGj2blzp3E6nUaSOX78eJl+rlSg/rmamJPK/gMsLCw0YWFhZvbs2WX2R0REmLvuust8/vnnZseOHeaTTz4xkkxWVlaZfkaNGmVuvPHGKtVU0y53nu655x4TExPjtu+bb74xksyuXbuMMedXWRISEszy5cvNv//9b7N7927TsGFD88ILL1TYb2FhoZF0xcLiz3n7eZKenm4klfkQ27hxY/P6669XbZAWecM5UlBQYHr06GFuu+22KxYGLsXbz5O///3vpnHjxqakpMR1XHFxsQkKCjKLFi2q+kAt8OR5MmHCBGOz2YyPj49rk2Tsdrvp3bt3jY+1qrzhvXOxC+dERYtmNe1Kvm9uuukmM3HiRLd9b775pgkMDHS9D+Li4sztt99uPv30U/PNN9+Yf//735V+0MrNzTWSzIYNG6pUX2W4hrqWad++vYqKisrs79ixo7Kzs3Xs2LEq91VaWup2DZQxRn/605/0j3/8Q//61790/fXXu7X/8ssvVVpaqlmzZumXv/yl2rRpU6O3nLlcNTknFXn33XdVXFys1NRUt/05OTk6evSo/vu//1s333yz2rZtW+Gt8AoLC7VkyRKNHj3acj2X43LnKTExUQcPHlRhYaFr365du2S329W8eXNJ0vr16/Xggw8qOTlZ8fHxcjgcOnLkyCXryc7OliQ1bdr0MkdUPd5+niQmJkqS260qjx07piNHjqhly5aWa6sKT58jBQUFuv322+Xv769ly5YpICCgBkdXNd5+npw8eVJ2u93t7hYXHlu5nrs6PHmeTJ48Wdu2bVN2drZrk6QXXnhB8+bNq8FRVo+n3zs/Z84vmFbpOueacCXfNxfO+YtduHOJMUZHjx7Vzp079cQTT+i2225Tu3btdPz48Ur7vfB+qbE5qpFYjhp35MgR06dPH/Pmm2+arVu3mr1795olS5aYJk2amFGjRhlj3D8FFhcXmzZt2pibb77ZrFu3znz77bfmvffec33ymjNnjlm2bJnZtWuX2bVrl/n73/9uQkNDzV/+8hfXa44dO9aEh4ebNWvWmLy8PNd24ddO2dnZRpKZPXu2+fbbb82CBQtMs2bNyqxQf/311yYrK8sMGjTI3HLLLSYrK6vc1VpPz4kxxlVb165dzV133WWysrLKvVTjpptuMsOGDSuz//Dhw8bf3988+uij5ttvvzVLly41bdq0KXeF+u9//7sJCAgodzW/JtX0PJ04ccI0b97c3Hnnnebrr782a9euNa1btzb33Xef6zU7d+5skpKSzDfffGM2bdpkbr75ZhMYGOhaQdmzZ4+ZNm2ayczMNPv27TNLly410dHR1f6tiifGb8zVO08GDx5s4uPjzfr168327dvNwIEDTfv27Wv8sgdvPEfy8/PNL37xC9OhQwezZ88et59B586dq9HxX4k5MObqnCc7duwwDofDjB071rUSl5qaasLDw83Bgwe9eo5q4jwpjypZiaxJ3jgn3377rZkxY4bJzMw0//nPf8z69evNoEGDTIMGDS55xylvGL8xlb9vpkyZYkJDQ82iRYvM3r17TUZGhomJiTEpKSnGmPPXlEdERJjU1FSze/dus3r1atOtWze3OjZt2mRefvllk5WVZfbv329Wr15tevbsaWJiYszp06drZG4I1F7q9OnTZvLkyaZLly4mPDzcBAUFmbi4OPPEE0+4Au7Pf4js37/fDB061ISFhZmgoCCTkJDg+sLLSy+9ZOLj401QUJAJCwsznTt3NnPnznX7taGkcrcL10UZY8zzzz9vmjZtagIDA02/fv3MggULygTqli1bltuPt81JRWNu2bKl2+vm5OQYSSYjI6PcuhYuXGhatWplHA6H6dGjh1m2bFm5gbpHjx7mrrvusjwPlbkS87Rjxw7Tt29fExgYaJo3b24efvhht+s1v/rqK5OQkGACAgJM69atzbvvvmtatmzp+oH/3XffmV69epkGDRoYh8NhYmNjzaOPPmry8/Nrxfiv1nmSn59vRo0aZerVq2caNGhghgwZ4nZ7tJrijefIZ599VuHPoH379tWKObha58mF6z/Dw8NN/fr1za233mo2btxYY3NzgTeeJ+W5moHaG+fk+++/N7/61a9M48aNjZ+fn2nevLm56667TE5OTq0Yf2Xvm7Nnz5qpU6eamJgYExAQYKKiosy4cePccseqVatMu3btjMPhMB07djRr1qxxq2Pbtm2mT58+rv+DWrVqZcaMGWMOHDhQY3Nj+9/BAAAAALgMXEMNAAAAWECgBgAAACwgUAMAAAAWEKgBAAAACwjUAAAAgAUEagAAAMACAjUAAABgAYEaAAAAsIBADQAAAFhAoAYAAAAsIFADAAAAFvx/4/xu/M+6G0MAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 800x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pred = [x in ntgenes for x in asubset.var.gene_symbol]\n",
+    "gf = asubset.var[pred]\n",
+    "\n",
+    "ntexp = create_expression_dataframe( asubset, gf )\n",
+    "agg = aggregate_by_metadata(ntexp, gf.gene_symbol, 'neurotransmitter')\n",
+    "plot_heatmap(agg,8,3,vmax=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[True, True, True, True, True, True, False, True, True, True]"
+      ]
+     },
+     "execution_count": 92,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pred"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>gene_symbol</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gene_identifier</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000037771</th>\n",
+       "      <td>Slc32a1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000070570</th>\n",
+       "      <td>Slc17a7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000039728</th>\n",
+       "      <td>Slc6a5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000030500</th>\n",
+       "      <td>Slc17a6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000055368</th>\n",
+       "      <td>Slc6a2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000019935</th>\n",
+       "      <td>Slc17a8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000020838</th>\n",
+       "      <td>Slc6a4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000021609</th>\n",
+       "      <td>Slc6a3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ENSMUSG00000100241</th>\n",
+       "      <td>Slc18a3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   gene_symbol\n",
+       "gene_identifier               \n",
+       "ENSMUSG00000037771     Slc32a1\n",
+       "ENSMUSG00000070570     Slc17a7\n",
+       "ENSMUSG00000039728      Slc6a5\n",
+       "ENSMUSG00000030500     Slc17a6\n",
+       "ENSMUSG00000055368      Slc6a2\n",
+       "ENSMUSG00000019935     Slc17a8\n",
+       "ENSMUSG00000020838      Slc6a4\n",
+       "ENSMUSG00000021609      Slc6a3\n",
+       "ENSMUSG00000100241     Slc18a3"
+      ]
+     },
+     "execution_count": 93,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cell_barcode</th>\n",
+       "      <th>barcoded_cell_sample_label</th>\n",
+       "      <th>library_label</th>\n",
+       "      <th>feature_matrix_label</th>\n",
+       "      <th>entity</th>\n",
+       "      <th>brain_section_label</th>\n",
+       "      <th>library_method</th>\n",
+       "      <th>region_of_interest_acronym</th>\n",
+       "      <th>donor_label</th>\n",
+       "      <th>donor_genotype</th>\n",
+       "      <th>...</th>\n",
+       "      <th>region_of_interest_color</th>\n",
+       "      <th>Slc32a1</th>\n",
+       "      <th>Slc17a7</th>\n",
+       "      <th>Slc6a5</th>\n",
+       "      <th>Slc17a6</th>\n",
+       "      <th>Slc6a2</th>\n",
+       "      <th>Slc17a8</th>\n",
+       "      <th>Slc6a4</th>\n",
+       "      <th>Slc6a3</th>\n",
+       "      <th>Slc18a3</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cell_label</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>CAGGTGCAGGCTAGCA-040_C01</th>\n",
+       "      <td>CAGGTGCAGGCTAGCA</td>\n",
+       "      <td>040_C01</td>\n",
+       "      <td>L8TX_180815_01_E08</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-404124</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>9.105261</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TGCGCAGGTTGCGCAC-045_C01</th>\n",
+       "      <td>TGCGCAGGTTGCGCAC</td>\n",
+       "      <td>045_C01</td>\n",
+       "      <td>L8TX_180829_01_C10</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-407905</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>7.724693</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CGATGTATCTTGCCGT-042_B01</th>\n",
+       "      <td>CGATGTATCTTGCCGT</td>\n",
+       "      <td>042_B01</td>\n",
+       "      <td>L8TX_180829_01_B09</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-407901</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>7.578836</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GACTAACGTCCTCTTG-040_B01</th>\n",
+       "      <td>GACTAACGTCCTCTTG</td>\n",
+       "      <td>040_B01</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-404124</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>6.765602</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GATCGTACAACTGCTA-040_B01</th>\n",
+       "      <td>GATCGTACAACTGCTA</td>\n",
+       "      <td>040_B01</td>\n",
+       "      <td>L8TX_180815_01_D08</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-404124</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>7.625302</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>6.632591</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTACTCCGTAGTACCT-103_B01</th>\n",
+       "      <td>GTACTCCGTAGTACCT</td>\n",
+       "      <td>103_B01</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GTGAAGGTCAGCTCTC-103_B01</th>\n",
+       "      <td>GTGAAGGTCAGCTCTC</td>\n",
+       "      <td>103_B01</td>\n",
+       "      <td>L8TX_190321_01_G03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>10.389612</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ACACCCTCATGCGCAC-103_C01</th>\n",
+       "      <td>ACACCCTCATGCGCAC</td>\n",
+       "      <td>103_C01</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CCTAAAGCAAGAGGCT-103_C01</th>\n",
+       "      <td>CCTAAAGCAAGAGGCT</td>\n",
+       "      <td>103_C01</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TCTGGAAAGATGAGAG-103_C01</th>\n",
+       "      <td>TCTGGAAAGATGAGAG</td>\n",
+       "      <td>103_C01</td>\n",
+       "      <td>L8TX_190321_01_H03</td>\n",
+       "      <td>WMB-10Xv2-TH</td>\n",
+       "      <td>cell</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10Xv2</td>\n",
+       "      <td>TH</td>\n",
+       "      <td>Snap25-IRES2-Cre;Ai14-449635</td>\n",
+       "      <td>Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt</td>\n",
+       "      <td>...</td>\n",
+       "      <td>#FF00EF</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>130555 rows × 36 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              cell_barcode barcoded_cell_sample_label   \n",
+       "cell_label                                                              \n",
+       "CAGGTGCAGGCTAGCA-040_C01  CAGGTGCAGGCTAGCA                    040_C01  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  TGCGCAGGTTGCGCAC                    045_C01   \n",
+       "CGATGTATCTTGCCGT-042_B01  CGATGTATCTTGCCGT                    042_B01   \n",
+       "GACTAACGTCCTCTTG-040_B01  GACTAACGTCCTCTTG                    040_B01   \n",
+       "GATCGTACAACTGCTA-040_B01  GATCGTACAACTGCTA                    040_B01   \n",
+       "...                                    ...                        ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  GTACTCCGTAGTACCT                    103_B01   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  GTGAAGGTCAGCTCTC                    103_B01   \n",
+       "ACACCCTCATGCGCAC-103_C01  ACACCCTCATGCGCAC                    103_C01   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  CCTAAAGCAAGAGGCT                    103_C01   \n",
+       "TCTGGAAAGATGAGAG-103_C01  TCTGGAAAGATGAGAG                    103_C01   \n",
+       "\n",
+       "                               library_label feature_matrix_label entity   \n",
+       "cell_label                                                                 \n",
+       "CAGGTGCAGGCTAGCA-040_C01  L8TX_180815_01_E08         WMB-10Xv2-TH   cell  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  L8TX_180829_01_C10         WMB-10Xv2-TH   cell   \n",
+       "CGATGTATCTTGCCGT-042_B01  L8TX_180829_01_B09         WMB-10Xv2-TH   cell   \n",
+       "GACTAACGTCCTCTTG-040_B01  L8TX_180815_01_D08         WMB-10Xv2-TH   cell   \n",
+       "GATCGTACAACTGCTA-040_B01  L8TX_180815_01_D08         WMB-10Xv2-TH   cell   \n",
+       "...                                      ...                  ...    ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  L8TX_190321_01_G03         WMB-10Xv2-TH   cell   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  L8TX_190321_01_G03         WMB-10Xv2-TH   cell   \n",
+       "ACACCCTCATGCGCAC-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+       "TCTGGAAAGATGAGAG-103_C01  L8TX_190321_01_H03         WMB-10Xv2-TH   cell   \n",
+       "\n",
+       "                          brain_section_label library_method   \n",
+       "cell_label                                                     \n",
+       "CAGGTGCAGGCTAGCA-040_C01                  NaN          10Xv2  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                  NaN          10Xv2   \n",
+       "CGATGTATCTTGCCGT-042_B01                  NaN          10Xv2   \n",
+       "GACTAACGTCCTCTTG-040_B01                  NaN          10Xv2   \n",
+       "GATCGTACAACTGCTA-040_B01                  NaN          10Xv2   \n",
+       "...                                       ...            ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                  NaN          10Xv2   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                  NaN          10Xv2   \n",
+       "ACACCCTCATGCGCAC-103_C01                  NaN          10Xv2   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                  NaN          10Xv2   \n",
+       "TCTGGAAAGATGAGAG-103_C01                  NaN          10Xv2   \n",
+       "\n",
+       "                         region_of_interest_acronym   \n",
+       "cell_label                                            \n",
+       "CAGGTGCAGGCTAGCA-040_C01                         TH  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                         TH   \n",
+       "CGATGTATCTTGCCGT-042_B01                         TH   \n",
+       "GACTAACGTCCTCTTG-040_B01                         TH   \n",
+       "GATCGTACAACTGCTA-040_B01                         TH   \n",
+       "...                                             ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                         TH   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                         TH   \n",
+       "ACACCCTCATGCGCAC-103_C01                         TH   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                         TH   \n",
+       "TCTGGAAAGATGAGAG-103_C01                         TH   \n",
+       "\n",
+       "                                           donor_label   \n",
+       "cell_label                                               \n",
+       "CAGGTGCAGGCTAGCA-040_C01  Snap25-IRES2-Cre;Ai14-404124  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  Snap25-IRES2-Cre;Ai14-407905   \n",
+       "CGATGTATCTTGCCGT-042_B01  Snap25-IRES2-Cre;Ai14-407901   \n",
+       "GACTAACGTCCTCTTG-040_B01  Snap25-IRES2-Cre;Ai14-404124   \n",
+       "GATCGTACAACTGCTA-040_B01  Snap25-IRES2-Cre;Ai14-404124   \n",
+       "...                                                ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "ACACCCTCATGCGCAC-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "TCTGGAAAGATGAGAG-103_C01  Snap25-IRES2-Cre;Ai14-449635   \n",
+       "\n",
+       "                                                donor_genotype  ...   \n",
+       "cell_label                                                      ...   \n",
+       "CAGGTGCAGGCTAGCA-040_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "CGATGTATCTTGCCGT-042_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "GACTAACGTCCTCTTG-040_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "GATCGTACAACTGCTA-040_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "...                                                        ...  ...   \n",
+       "GTACTCCGTAGTACCT-103_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "GTGAAGGTCAGCTCTC-103_B01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "ACACCCTCATGCGCAC-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "CCTAAAGCAAGAGGCT-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "TCTGGAAAGATGAGAG-103_C01  Snap25-IRES2-Cre/wt;Ai14(RCL-tdT)/wt  ...   \n",
+       "\n",
+       "                         region_of_interest_color   Slc32a1    Slc17a7   \n",
+       "cell_label                                                               \n",
+       "CAGGTGCAGGCTAGCA-040_C01                  #FF00EF  9.105261   0.000000  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01                  #FF00EF  7.724693   0.000000   \n",
+       "CGATGTATCTTGCCGT-042_B01                  #FF00EF  7.578836   0.000000   \n",
+       "GACTAACGTCCTCTTG-040_B01                  #FF00EF  6.765602   0.000000   \n",
+       "GATCGTACAACTGCTA-040_B01                  #FF00EF  7.625302   0.000000   \n",
+       "...                                           ...       ...        ...   \n",
+       "GTACTCCGTAGTACCT-103_B01                  #FF00EF  0.000000   0.000000   \n",
+       "GTGAAGGTCAGCTCTC-103_B01                  #FF00EF  0.000000  10.389612   \n",
+       "ACACCCTCATGCGCAC-103_C01                  #FF00EF  0.000000   0.000000   \n",
+       "CCTAAAGCAAGAGGCT-103_C01                  #FF00EF  0.000000   0.000000   \n",
+       "TCTGGAAAGATGAGAG-103_C01                  #FF00EF  0.000000   0.000000   \n",
+       "\n",
+       "                          Slc6a5   Slc17a6 Slc6a2 Slc17a8 Slc6a4 Slc6a3   \n",
+       "cell_label                                                                \n",
+       "CAGGTGCAGGCTAGCA-040_C01     0.0  0.000000    0.0     0.0    0.0    0.0  \\\n",
+       "TGCGCAGGTTGCGCAC-045_C01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "CGATGTATCTTGCCGT-042_B01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "GACTAACGTCCTCTTG-040_B01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "GATCGTACAACTGCTA-040_B01     0.0  6.632591    0.0     0.0    0.0    0.0   \n",
+       "...                          ...       ...    ...     ...    ...    ...   \n",
+       "GTACTCCGTAGTACCT-103_B01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "GTGAAGGTCAGCTCTC-103_B01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "ACACCCTCATGCGCAC-103_C01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "CCTAAAGCAAGAGGCT-103_C01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "TCTGGAAAGATGAGAG-103_C01     0.0  0.000000    0.0     0.0    0.0    0.0   \n",
+       "\n",
+       "                         Slc18a3  \n",
+       "cell_label                        \n",
+       "CAGGTGCAGGCTAGCA-040_C01     0.0  \n",
+       "TGCGCAGGTTGCGCAC-045_C01     0.0  \n",
+       "CGATGTATCTTGCCGT-042_B01     0.0  \n",
+       "GACTAACGTCCTCTTG-040_B01     0.0  \n",
+       "GATCGTACAACTGCTA-040_B01     0.0  \n",
+       "...                          ...  \n",
+       "GTACTCCGTAGTACCT-103_B01     0.0  \n",
+       "GTGAAGGTCAGCTCTC-103_B01     0.0  \n",
+       "ACACCCTCATGCGCAC-103_C01     0.0  \n",
+       "CCTAAAGCAAGAGGCT-103_C01     0.0  \n",
+       "TCTGGAAAGATGAGAG-103_C01     0.0  \n",
+       "\n",
+       "[130555 rows x 36 columns]"
+      ]
+     },
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ntexp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['cell_barcode', 'barcoded_cell_sample_label', 'library_label', 'feature_matrix_label', 'entity', 'brain_section_label', 'library_method', 'region_of_interest_acronym', 'donor_label', 'donor_genotype', 'donor_sex', 'dataset_label', 'x', 'y', 'cluster_alias', 'neurotransmitter', 'class', 'subclass', 'supertype', 'cluster', 'neurotransmitter_color', 'class_color', 'subclass_color', 'supertype_color', 'cluster_color', 'region_of_interest_order', 'region_of_interest_color', 'Slc32a1', 'Slc17a7', 'Slc6a5', 'Slc17a6', 'Slc6a2', 'Slc17a8', 'Slc6a4', 'Slc6a3', 'Slc18a3']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ntexp.columns.to_list())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Slc32a1</th>\n",
+       "      <th>Slc17a7</th>\n",
+       "      <th>Slc6a5</th>\n",
+       "      <th>Slc17a6</th>\n",
+       "      <th>Slc6a2</th>\n",
+       "      <th>Slc17a8</th>\n",
+       "      <th>Slc6a4</th>\n",
+       "      <th>Slc6a3</th>\n",
+       "      <th>Slc18a3</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>neurotransmitter</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <td>0.046035</td>\n",
+       "      <td>0.344887</td>\n",
+       "      <td>0.001850</td>\n",
+       "      <td>0.987392</td>\n",
+       "      <td>0.001738</td>\n",
+       "      <td>0.006960</td>\n",
+       "      <td>0.001023</td>\n",
+       "      <td>0.003902</td>\n",
+       "      <td>0.001430</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Chol</th>\n",
+       "      <td>0.055375</td>\n",
+       "      <td>8.177763</td>\n",
+       "      <td>0.004191</td>\n",
+       "      <td>6.245038</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.053680</td>\n",
+       "      <td>0.008561</td>\n",
+       "      <td>0.004247</td>\n",
+       "      <td>2.921945</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dopa</th>\n",
+       "      <td>1.667179</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>6.288765</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.966069</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GABA</th>\n",
+       "      <td>7.170930</td>\n",
+       "      <td>0.419358</td>\n",
+       "      <td>0.026198</td>\n",
+       "      <td>1.207092</td>\n",
+       "      <td>0.001387</td>\n",
+       "      <td>0.033399</td>\n",
+       "      <td>0.010815</td>\n",
+       "      <td>0.016633</td>\n",
+       "      <td>0.000965</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>GABA-Glyc</th>\n",
+       "      <td>6.506756</td>\n",
+       "      <td>0.325198</td>\n",
+       "      <td>3.977854</td>\n",
+       "      <td>1.478667</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.139776</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Glut</th>\n",
+       "      <td>0.080621</td>\n",
+       "      <td>3.388569</td>\n",
+       "      <td>0.035605</td>\n",
+       "      <td>9.013955</td>\n",
+       "      <td>0.001369</td>\n",
+       "      <td>0.234089</td>\n",
+       "      <td>0.009263</td>\n",
+       "      <td>0.004076</td>\n",
+       "      <td>0.014749</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Glut-GABA</th>\n",
+       "      <td>3.311663</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>7.546851</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   Slc32a1   Slc17a7    Slc6a5   Slc17a6    Slc6a2   Slc17a8   \n",
+       "neurotransmitter                                                               \n",
+       "                  0.046035  0.344887  0.001850  0.987392  0.001738  0.006960  \\\n",
+       "Chol              0.055375  8.177763  0.004191  6.245038  0.000000  0.053680   \n",
+       "Dopa              1.667179  0.000000  0.000000  6.288765  0.000000  0.000000   \n",
+       "GABA              7.170930  0.419358  0.026198  1.207092  0.001387  0.033399   \n",
+       "GABA-Glyc         6.506756  0.325198  3.977854  1.478667  0.000000  0.000000   \n",
+       "Glut              0.080621  3.388569  0.035605  9.013955  0.001369  0.234089   \n",
+       "Glut-GABA         3.311663  0.000000  0.000000  7.546851  0.000000  0.000000   \n",
+       "\n",
+       "                    Slc6a4    Slc6a3   Slc18a3  \n",
+       "neurotransmitter                                \n",
+       "                  0.001023  0.003902  0.001430  \n",
+       "Chol              0.008561  0.004247  2.921945  \n",
+       "Dopa              0.000000  4.966069  0.000000  \n",
+       "GABA              0.010815  0.016633  0.000965  \n",
+       "GABA-Glyc         0.000000  0.139776  0.000000  \n",
+       "Glut              0.009263  0.004076  0.014749  \n",
+       "Glut-GABA         0.000000  0.000000  0.000000  "
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agg"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "--------#Fix: Now let's do this with tiledbsoma------"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# def merge_tiledb_data(query):\n",
+    "#     # Convert the TileDB data to AnnData\n",
+    "#     try:\n",
+    "#         adata = query.to_anndata(X_name=\"data\")\n",
+    "#     except Exception as e:\n",
+    "#         print(f\"Exception encountered: {e}\")\n",
+    "#         return None\n",
+    "\n",
+    "#     # Convert AnnData to DataFrame\n",
+    "#     expression_df = pd.DataFrame(adata.X.todense(), columns=adata.var.index, index=adata.obs.index)\n",
+    "    \n",
+    "#     # Fetch separate obs and var data\n",
+    "#     obs_data = query.obs().concat().to_pandas()\n",
+    "#     var_data = query.var().concat().to_pandas()\n",
+    "    \n",
+    "#     # For demonstration, just return the head of expression DataFrame\n",
+    "#     return expression_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# merged_data = merge_tiledb_data(query)\n",
+    "# if merged_data is not None:\n",
+    "#     print(merged_data.head())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# import pandas as pd\n",
+    "\n",
+    "# def merge_tiledb_data(query):\n",
+    "#     # Shape from TileDB\n",
+    "#     n_obs, n_var = query.n_obs, query.n_vars\n",
+    "#     print(\"Number of observations:\", n_obs)\n",
+    "#     print(\"Number of variables:\", n_var)\n",
+    "    \n",
+    "#     # Fetch separate data\n",
+    "#     obs_data = query.obs().concat().to_pandas()\n",
+    "#     print(\"Observation Data:\", obs_data.head())\n",
+    "    \n",
+    "#     var_data = query.var().concat().to_pandas()\n",
+    "#     print(\"Variable Data:\", var_data.head())\n",
+    "    \n",
+    "#     # Read the SparseNDArray and try converting to scipy sparse matrix\n",
+    "#     X = query.X(layer_name=\"data\")\n",
+    "#     try:\n",
+    "#         coo_data = X.coos((n_obs, n_var)).concat()\n",
+    "        \n",
+    "#         # Check if indices are within bounds\n",
+    "#         if coo_data.row_indices.max() >= n_obs or coo_data.column_indices.max() >= n_var:\n",
+    "#             print(\"Indices exceed matrix dimensions. Cannot proceed.\")\n",
+    "#             return None\n",
+    "        \n",
+    "#         expression_data = coo_data.to_scipy().tocoo()\n",
+    "#     except Exception as e:\n",
+    "#         print(f\"Exception encountered: {e}\")\n",
+    "#         return None\n",
+    "    \n",
+    "#     # Convert to DataFrame for easier merging\n",
+    "#     expression_df = pd.DataFrame({\n",
+    "#         'soma_dim_0': expression_data.row,\n",
+    "#         'soma_dim_1': expression_data.col,\n",
+    "#         'soma_data': expression_data.data\n",
+    "#     })\n",
+    "    \n",
+    "#     print(\"Expression Data:\", expression_df.head())\n",
+    "    \n",
+    "#     # Merge the data\n",
+    "#     merged_with_obs = pd.merge(expression_df, obs_data, how='inner', left_on='soma_dim_0', right_index=True)\n",
+    "#     merged_with_var = pd.merge(expression_df, var_data, how='inner', left_on='soma_dim_1', right_index=True)\n",
+    "#     final_merged_data = pd.merge(merged_with_obs, merged_with_var, how='inner', on=['soma_dim_0', 'soma_dim_1', 'soma_data'])\n",
+    "    \n",
+    "#     return final_merged_data\n",
+    "\n",
+    "# # Assuming 'query' is the ExperimentAxisQuery object you've constructed\n",
+    "# merged_data = merge_tiledb_data(query)\n",
+    "# if merged_data is not None:\n",
+    "#     print(merged_data.head())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# def create_tiledb_expression_dataframe(query, filtered_gene_ids, cell_filtered, gene_id_to_symbol_mapping):\n",
+    "#     expression_data = query.X(layer_name=\"data\").tables().concat().to_pandas()\n",
+    "#     print(\"Expression Data:\")\n",
+    "#     print(expression_data.head())\n",
+    "    \n",
+    "#     # Filter the expression data using gene IDs\n",
+    "#     expression_data_filtered = expression_data[expression_data['soma_dim_1'].isin(filtered_gene_ids)]\n",
+    "    \n",
+    "#     if expression_data_filtered.empty:\n",
+    "#         print(\"Filtered Expression Data is empty.\")\n",
+    "#         return None\n",
+    "    \n",
+    "#     meta_data = query.obs(column_names=[\"soma_joinid\", \"cell_label\", \"anatomical_division_label\"]).concat().to_pandas()\n",
+    "#     print(\"Meta Data:\")\n",
+    "#     print(meta_data.head())\n",
+    "    \n",
+    "#     # Pivot the filtered expression data\n",
+    "#     expression_data_pivot = expression_data_filtered.pivot(index='soma_dim_0', columns='soma_dim_1', values='soma_data')\n",
+    "#     if expression_data_pivot.empty:\n",
+    "#         print(\"Pivoted Expression Data is empty.\")\n",
+    "#         return None\n",
+    "    \n",
+    "#     print(\"Pivoted Expression Data:\")\n",
+    "#     print(expression_data_pivot.head())\n",
+    "    \n",
+    "#     # Rename the columns\n",
+    "#     expression_data_pivot.rename(columns=gene_id_to_symbol_mapping, inplace=True)\n",
+    "#     print(\"Column-renamed Pivoted Expression Data:\")\n",
+    "#     print(expression_data_pivot.head())\n",
+    "    \n",
+    "#     # Merge meta_data with pivoted expression data\n",
+    "#     if 'soma_joinid' not in meta_data.columns:\n",
+    "#         print(\"Meta Data does not contain 'soma_joinid'. Cannot proceed with merge.\")\n",
+    "#         return None\n",
+    "    \n",
+    "#     merged_data = pd.merge(meta_data, expression_data_pivot, left_on='soma_joinid', right_index=True, how='inner')\n",
+    "#     print(\"Merged Meta and Expression Data:\")\n",
+    "#     print(merged_data.head())\n",
+    "    \n",
+    "#     # Merge with cell_filtered DataFrame\n",
+    "#     if 'soma_joinid' not in cell_filtered.columns:\n",
+    "#         print(\"cell_filtered does not contain 'soma_joinid'. Cannot proceed with merge.\")\n",
+    "#         return None\n",
+    "    \n",
+    "#     joined = pd.merge(cell_filtered, merged_data, on='soma_joinid', how='inner')\n",
+    "#     print(\"Joined Data:\")\n",
+    "#     print(joined.head())\n",
+    "    \n",
+    "#     return joined\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# def aggregate_by_metadata(df, gnames, value, sort=False):\n",
+    "#     grouped = df.groupby(value)[gnames].mean()\n",
+    "#     if sort:\n",
+    "#         grouped = grouped.sort_values(by=gnames[0], ascending=False)\n",
+    "#     return grouped\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# # Create the mapping dictionary from the variable metadata\n",
+    "# var_metadata = query.var().concat().to_pandas()\n",
+    "# gene_id_to_symbol_mapping = dict(zip(var_metadata['soma_joinid'], var_metadata['gene_symbol']))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# print(gene_id_to_symbol_mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# # Get the gene symbols of all genes.\n",
+    "# gene_symbols_and_identifiers = tdbs.ms[\"RNA\"].var.read().concat().to_pandas()\n",
+    "\n",
+    "# # Create a list of genes to filter.\n",
+    "# genes_to_filter = [\"Slc17a7\", \"Slc17a6\", \"Slc17a8\", \"Slc32a1\", \"Slc6a5\", \"Slc18a3\", \"Slc6a3\", \"Slc6a4\", \"Slc6a2\", \"Tac2\"]\n",
+    "\n",
+    "# # Filter the gene symbols and identifiers based on the list of genes to filter.\n",
+    "# filtered_gene_symbols_and_identifiers = gene_symbols_and_identifiers[gene_symbols_and_identifiers[\"gene_symbol\"].isin(genes_to_filter)]\n",
+    "\n",
+    "# # Print the filtered gene symbols and identifiers.\n",
+    "# print(filtered_gene_symbols_and_identifiers)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# filtered_gene_ids = filtered_gene_symbols_and_identifiers['soma_joinid'].tolist()\n",
+    "# print(filtered_gene_ids)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# # Assuming cell_filtered, filtered_gene_symbols, and gene_id_to_symbol_mapping are available\n",
+    "# tiledb_ntexp = create_tiledb_expression_dataframe(query, filtered_gene_ids, cell_filtered, gene_id_to_symbol_mapping)\n",
+    "# tiledb_agg = aggregate_by_metadata(tiledb_ntexp, filtered_gene_symbols, 'neurotransmitter')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# print(tiledb_ntexp)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# print(tiledb_agg)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Expression of Tachykinin 2 (Tac2) in the thalamus\n",
+    "\n",
+    "In mice, the tachykinin 2 (Tac2) gene encodes neuropeptide called neurokinin B (NkB). Tac2 is produced by neurons in specific regions of the brain know to be invovled in emotion and social behavior. Based on [ISH data](https://mouse.brain-map.org/experiment/siv?id=77279001&imageId=77284584&initImage=ish&coordSystem=pixel&x=5384.5&y=3832.5&z=3) from the Allen Mouse Brain Atlas, Tac 2 is sparsely expressed in the mouse isocortex and densely enriched is specific subcortical regions such the medial habenula (MH), the amygdala and hypothalamus.\n",
+    "\n",
+    "In this example, we create a dataframe comprising of cells in the 'WMB-10Xv2-TH' package and expression values of Tac2 in those cells."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gf = asubset.var[asubset.var.gene_symbol == 'Tac2']\n",
+    "tac2 = create_expression_dataframe( asubset, gf )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Grouping cells by neurotransmitter identites and computing the mean expression in each group, we can observed that Tac2 gene is highly enriched in cholinergic cell types."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 100x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "agg = aggregate_by_metadata(tac2, gf.gene_symbol, 'neurotransmitter', True).head(10)\n",
+    "plot_heatmap(agg,1,3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Grouping cells by cell types class, shows that Tac2 is enriched in class \"16 MH-LH Glut\" with cells restricted to the medial (MH) and lateral (LH) habenula and a mixture of glutamatergic and cholinergic types."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 100x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "agg = aggregate_by_metadata(tac2, gf.gene_symbol, 'class', True).head(8)\n",
+    "plot_heatmap(agg,1,3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "At the next level, grouping by subclass, shows Tac2 is enriched in sublcass \"145 MH Tac2 Glut\" with further specificity to the medial habenula and with Tac2 itself as a marker for the subclass."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 100x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "agg = aggregate_by_metadata(tac2, gf.gene_symbol, 'subclass',True).head(8)\n",
+    "plot_heatmap(agg,1,3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next level down, gene Tac2 is enriched in several children supertypes of \"145 MH Tac2 Glut\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 100x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "agg = aggregate_by_metadata(tac2, gf.gene_symbol, 'supertype',True).head(10)\n",
+    "plot_heatmap(agg,1,3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Close h5ad file and clean up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "adata.file.close()\n",
+    "del adata"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "TDB",
+   "language": "python",
+   "name": "tdb"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/convert_WMB-10Xv2_to_TDBsoma.ipynb b/notebooks/convert_WMB-10Xv2_to_TDBsoma.ipynb
new file mode 100644
index 00000000..e19c345e
--- /dev/null
+++ b/notebooks/convert_WMB-10Xv2_to_TDBsoma.ipynb
@@ -0,0 +1,570 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2e7673d3-ed4f-40f0-b64b-b46afe453922",
+   "metadata": {},
+   "source": [
+    "# Code for converting H5AD files to TDB\n",
+    "### At the beginning of this file, please indicate whether you want to convert raw or log2 files to TDB.\n",
+    "### At the end of this file, the terminal output is saved to a log file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ec3a2555-9a3f-4765-a53f-744cedb4e86f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Specify the file type to convert: 'both', 'raw', or 'log2'\n",
+    "file_type_to_convert = 'log2' #'both'  or 'raw' or 'log2'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17687871-bbc3-4735-8d7e-77eafd15f3cc",
+   "metadata": {},
+   "source": [
+    "## Preliminary Steps\n",
+    "Import Libraries: Necessary Python packages like anndata, tiledb, logging, etc., are imported.\n",
+    "Print Versions: TileDB versions are printed for debugging and traceability.\n",
+    "Specify Directories: input_dir and output_dir are specified.\n",
+    "List Files: All files in the input_dir are printed for a visual display."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2cbc13a0-af5f-4f8e-a609-f9e7b5c837c6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Import libraries\n",
+    "import logging\n",
+    "import io\n",
+    "import sys\n",
+    "import os\n",
+    "import numpy as np\n",
+    "import anndata as ad\n",
+    "import pandas as pd\n",
+    "import tiledb\n",
+    "import tiledbsoma\n",
+    "import tiledbsoma.io\n",
+    "import tiledbsoma.logging\n",
+    "import logging\n",
+    "# from concurrent.futures import ThreadPoolExecutor # For later for parallel conversion\n",
+    "from tqdm import tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "78cb8c4d-37d8-43e3-a253-f98a2ed72215",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TileDB core version: (2, 15, 2)\n",
+      "TileDB-Py v(0, 21, 3) TileDB-SOMA v1.2.2\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print versions for debugging and traceability\n",
+    "print(\"TileDB core version: {}\".format(tiledb.libtiledb.version()))\n",
+    "print(f\"\"\"TileDB-Py v{tiledb.version()} TileDB-SOMA v{tiledbsoma.__version__}\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "716a4ec8-65bc-4f00-82d3-ee9ee93b5eea",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input directory: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630\n",
+      "Output directory: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630\n"
+     ]
+    }
+   ],
+   "source": [
+    "download_base = '/shared/Data/abc_download_root'\n",
+    "# input and output directories\n",
+    "input_dir = download_base + \"/expression_matrices/WMB-10Xv2/20230630\"\n",
+    "output_dir = download_base + \"/expression_matrices/WMB-10Xv2-TDB/20230630\"\n",
+    "print(f\"Input directory: {input_dir}\")\n",
+    "print(f\"Output directory: {output_dir}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "697b1f32-3956-4ce7-bb92-f736e97c7038",
+   "metadata": {},
+   "source": [
+    "## File Listing with Sizes\n",
+    "Initialize Lists: Two lists raw_files and log2_files are initialized to store filenames with sizes.\n",
+    "Check File Sizes: For each file in the input_dir, if it's a raw or log2 file, its size in GB is calculated and stored alongside the filename in the corresponding list."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "84816bc1-b561-4a12-9ec8-56785da81fd0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WMB-10Xv2-Isocortex-1-log2.h5ad\n",
+      "WMB-10Xv2-HPF-log2.h5ad\n",
+      "WMB-10Xv2-Isocortex-3-raw.h5ad\n",
+      "WMB-10Xv2-CTXsp-log2.h5ad\n",
+      "WMB-10Xv2-TH-raw.h5ad\n",
+      "WMB-10Xv2-Isocortex-3-log2.h5ad\n",
+      "WMB-10Xv2-CTXsp-raw.h5ad\n",
+      "WMB-10Xv2-Isocortex-1-raw.h5ad\n",
+      "WMB-10Xv2-HPF-raw.h5ad\n",
+      "WMB-10Xv2-TH-log2.h5ad\n",
+      "WMB-10Xv2-MB-log2.h5ad\n",
+      "WMB-10Xv2-Isocortex-2-log2.h5ad\n",
+      "WMB-10Xv2-HY-raw.h5ad\n",
+      "WMB-10Xv2-Isocortex-4-raw.h5ad\n",
+      "WMB-10Xv2-OLF-raw.h5ad\n",
+      "WMB-10Xv2-HY-log2.h5ad\n",
+      "WMB-10Xv2-Isocortex-4-log2.h5ad\n",
+      "WMB-10Xv2-OLF-log2.h5ad\n",
+      "WMB-10Xv2-MB-raw.h5ad\n",
+      "WMB-10Xv2-Isocortex-2-raw.h5ad\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get a list of files for visual display\n",
+    "for filename in (os.listdir(input_dir)):\n",
+    "    print(filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7196ea8f-7154-40c4-aa99-6776e141e5bc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Raw Files                                         Log2 Files                                        \n",
+      "====================================================================================================\n",
+      "WMB-10Xv2-Isocortex-3-raw.h5ad (7.88 GB)          WMB-10Xv2-Isocortex-1-log2.h5ad (8.01 GB)         \n",
+      "WMB-10Xv2-TH-raw.h5ad (3.76 GB)                   WMB-10Xv2-HPF-log2.h5ad (5.68 GB)                 \n",
+      "WMB-10Xv2-CTXsp-raw.h5ad (1.62 GB)                WMB-10Xv2-CTXsp-log2.h5ad (1.62 GB)               \n",
+      "WMB-10Xv2-Isocortex-1-raw.h5ad (8.01 GB)          WMB-10Xv2-Isocortex-3-log2.h5ad (7.88 GB)         \n",
+      "WMB-10Xv2-HPF-raw.h5ad (5.68 GB)                  WMB-10Xv2-TH-log2.h5ad (3.76 GB)                  \n",
+      "WMB-10Xv2-HY-raw.h5ad (2.71 GB)                   WMB-10Xv2-MB-log2.h5ad (0.76 GB)                  \n",
+      "WMB-10Xv2-Isocortex-4-raw.h5ad (8.10 GB)          WMB-10Xv2-Isocortex-2-log2.h5ad (8.80 GB)         \n",
+      "WMB-10Xv2-OLF-raw.h5ad (4.78 GB)                  WMB-10Xv2-HY-log2.h5ad (2.71 GB)                  \n",
+      "WMB-10Xv2-MB-raw.h5ad (0.76 GB)                   WMB-10Xv2-Isocortex-4-log2.h5ad (8.10 GB)         \n",
+      "WMB-10Xv2-Isocortex-2-raw.h5ad (8.80 GB)          WMB-10Xv2-OLF-log2.h5ad (4.78 GB)                 \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize lists to hold filenames and sizes\n",
+    "raw_files = []\n",
+    "log2_files = []\n",
+    "\n",
+    "# Function to get file size in GB\n",
+    "def get_size_in_gb(file_path):\n",
+    "    size_bytes = os.path.getsize(file_path)\n",
+    "    size_gb = size_bytes / (1024 ** 3)\n",
+    "    return f\"{size_gb:.2f} GB\"\n",
+    "\n",
+    "# Get a list of files for visual display\n",
+    "for filename in os.listdir(input_dir):\n",
+    "    full_path = os.path.join(input_dir, filename)\n",
+    "    if filename.endswith(\"raw.h5ad\"):\n",
+    "        size = get_size_in_gb(full_path)\n",
+    "        raw_files.append(f\"{filename} ({size})\")\n",
+    "    elif filename.endswith(\"log2.h5ad\"):\n",
+    "        size = get_size_in_gb(full_path)\n",
+    "        log2_files.append(f\"{filename} ({size})\")\n",
+    "\n",
+    "# Print filenames in two columns: raw and log2\n",
+    "print(f\"{'Raw Files':<50}{'Log2 Files':<50}\")\n",
+    "print(\"=\" * 100)\n",
+    "\n",
+    "# Determine the maximum number of rows to print\n",
+    "max_rows = max(len(raw_files), len(log2_files))\n",
+    "\n",
+    "# Print the filenames and sizes side by side\n",
+    "for i in range(max_rows):\n",
+    "    raw_file = raw_files[i] if i < len(raw_files) else ''\n",
+    "    log2_file = log2_files[i] if i < len(log2_files) else ''\n",
+    "    print(f\"{raw_file:<50}{log2_file:<50}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15baac3c-4f28-4c86-8a95-f8e59a18d326",
+   "metadata": {},
+   "source": [
+    "## Logging Setup\n",
+    "Initialize Logging: Logging is set up to capture messages at the INFO level.\n",
+    "Log File: A conversion_all.log file is created in a conversionLog directory under output_dir. This file will capture all the logging messages."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "dcc16889-7963-42eb-b4a2-07a656f6e027",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2023-09-23 17:31:23,296 - INFO - Starting conversion...\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize logging\n",
+    "conversion_log_dir = os.path.join(output_dir, \"conversionLog\")\n",
+    "\n",
+    "# Create the conversionLog directory if it doesn't exist\n",
+    "if not os.path.exists(conversion_log_dir):\n",
+    "    os.makedirs(conversion_log_dir)\n",
+    "\n",
+    "# Setup Python logging\n",
+    "logging.basicConfig(level=logging.INFO,\n",
+    "                    format='%(asctime)s - %(levelname)s - %(message)s',\n",
+    "                    handlers=[logging.FileHandler(os.path.join(conversion_log_dir, 'conversion_all.log'), 'w', 'utf-8'),\n",
+    "                              logging.StreamHandler()])\n",
+    "\n",
+    "logging.info(\"Starting conversion...\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b61a80ab-1432-44b8-a207-921079c8d4dd",
+   "metadata": {},
+   "source": [
+    "Counters Initialization\n",
+    "Initialize Counters: Counters for completed_files and total_files are initialized to keep track of conversion progress."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "22e3a2a0-c021-4dac-951b-e7be9af4722f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Initialize counters for completed files and total files\n",
+    "completed_files = {'raw': 0, 'log2': 0}\n",
+    "total_files = {'raw': len([f for f in os.listdir(input_dir) if f.endswith(\"raw.h5ad\")]),\n",
+    "               'log2': len([f for f in os.listdir(input_dir) if f.endswith(\"log2.h5ad\")])}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1eac6875-9a05-4e35-a1e4-023d55d63552",
+   "metadata": {},
+   "source": [
+    "## The Conversion Function (convert_file)\n",
+    "File Type Check: Validates the file_type argument and logs an error if invalid.\n",
+    "Conversion: Checks if the file should be converted based on its suffix and the file_type argument.\n",
+    "Buffer Size: Dynamically sets the TileDB buffer size based on the size of the AnnData object.\n",
+    "Column Check: Checks for and removes columns with non-ASCII characters in the AnnData object.\n",
+    "TileDB Conversion: Calls tiledbsoma.io.from_anndata() to convert the AnnData object to a TileDB array.\n",
+    "Progress Logging: Logs the conversion progress to both the terminal and the conversion_all.log file.\n",
+    "TileDB Logging: Captures TileDB-specific logging into individual log files, one for each converted file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4b8c2dfb-54c1-4fdf-a7eb-9cb84a6e772a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Function to convert a single file\n",
+    "def convert_file(filename, file_type='both'):\n",
+    "    try:\n",
+    "        if file_type not in ['both', 'raw', 'log2']:\n",
+    "            logging.error(\"Invalid file_type. Use 'both', 'raw', or 'log2'\")\n",
+    "            return\n",
+    "        \n",
+    "        if (filename.endswith(\"raw.h5ad\") and file_type in ['both', 'raw']) or \\\n",
+    "           (filename.endswith(\"log2.h5ad\") and file_type in ['both', 'log2']):\n",
+    "            \n",
+    "            key = 'raw' if filename.endswith(\"raw.h5ad\") else 'log2'\n",
+    "            \n",
+    "            fname = os.path.join(input_dir, filename)\n",
+    "            uri = os.path.join(output_dir, os.path.splitext(filename)[0])\n",
+    "\n",
+    "            logging.info(f\"Starting conversion: {fname} to {uri}\")\n",
+    "\n",
+    "            if os.path.exists(uri):\n",
+    "                logging.info(f\"Output file {uri} already exists. Skipping.\")\n",
+    "                return\n",
+    "\n",
+    "            adata = ad.read_h5ad(fname, 'r')\n",
+    "\n",
+    "            # Update buffer size dynamically based on the AnnData object size\n",
+    "            # Calculate the size of the AnnData object's X attribute in bytes\n",
+    "            adata_nbytes = adata.X.nbytes if hasattr(adata.X, 'nbytes') else 0\n",
+    "            # Calculate the dynamic buffer size\n",
+    "            buffer_size = min(50 * 1024**2, adata_nbytes * 2)\n",
+    "            # Update the config with the new buffer size\n",
+    "            cfg = tiledb.Ctx().config()\n",
+    "            cfg.update({'py.init_buffer_bytes': buffer_size})\n",
+    "\n",
+    "            for col in adata.obs.select_dtypes(include=[pd.CategoricalDtype]).columns:\n",
+    "                if adata.obs[col].str.contains(r'[^\\x00-\\x7F]+').any():\n",
+    "                    logging.warning(f\"Column '{col}' in file {filename} contains records with non-ASCII characters. Removing column.\")\n",
+    "                    adata.obs.drop(col, axis=1, inplace=True)\n",
+    "\n",
+    "            tiledbsoma.io.from_anndata(uri, adata, measurement_name=\"RNA\")\n",
+    "            \n",
+    "            # Increment and display the counter\n",
+    "            completed_files[key] += 1\n",
+    "            logging.info(f\"Successfully converted {filename} to {uri}. Progress: {completed_files[key]}/{total_files[key]}\")\n",
+    "\n",
+    "            # Save tiledb-specific logging output to individual log file\n",
+    "            log_file = os.path.join(conversion_log_dir, f\"{os.path.splitext(filename)[0]}.log\")\n",
+    "            with open(log_file, 'w') as f:\n",
+    "                f.write(tiledbsoma.logging.info())                 \n",
+    "                \n",
+    "    except Exception as e:\n",
+    "        logging.error(f\"An error occurred while processing {filename}: {e}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "916c28f0-fd53-4dbb-9137-6a19c3fd2ce1",
+   "metadata": {},
+   "source": [
+    "## Run &Capturing Terminal Output\n",
+    "Capture stdout: The standard output is captured into a StringIO object.\n",
+    "Run Conversion: The convert_file function is called for each file in the input_dir while displaying a progress bar.\n",
+    "Restore stdout: The standard output is restored.\n",
+    "Save Captured Output: The captured terminal output is saved into a log file named conversion_terminal_output.log in the output_dir.\n",
+    "### Output & Logging\n",
+    "Terminal: You will see logging messages and a progress bar.\n",
+    "conversion_all.log: This file will contain all the logging messages.\n",
+    "Individual Log Files: TileDB-specific logging for each file will be saved in individual .log files in the conversionLog directory.\n",
+    "conversion_terminal_output.log: This will contain everything that was printed to the terminal."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c5af70bf-9979-402e-bf71-e8c3128b3721",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/20 [00:00<?, ?it/s]2023-09-23 17:31:23,540 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-1-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-1-log2\n",
+      "2023-09-23 17:37:37,927 - INFO - Successfully converted WMB-10Xv2-Isocortex-1-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-1-log2. Progress: 1/10\n",
+      "2023-09-23 17:37:37,938 - ERROR - An error occurred while processing WMB-10Xv2-Isocortex-1-log2.h5ad: write() argument must be str, not None\n",
+      "  5%|▌         | 1/20 [06:14<1:58:33, 374.40s/it]2023-09-23 17:37:37,940 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HPF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2\n",
+      "2023-09-23 17:37:40,014 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2/obs\n",
+      "2023-09-23 17:37:41,875 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2/ms/RNA/uns (uns collection)\n",
+      "2023-09-23 17:37:42,679 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2/ms/RNA/var\n",
+      "2023-09-23 17:37:42,879 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:39:18,792 - INFO - ...  30.744% done, ETA 3.60 minutes\n",
+      "2023-09-23 17:40:16,109 - INFO - ...  54.221% done, ETA 1.86 minutes\n",
+      "2023-09-23 17:41:22,797 - INFO - ...  82.424% done, ETA 42.46 seconds\n",
+      "2023-09-23 17:42:16,497 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:42:16,586 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2\n",
+      "2023-09-23 17:42:16,587 - INFO - Successfully converted WMB-10Xv2-HPF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HPF-log2. Progress: 2/10\n",
+      "2023-09-23 17:42:16,594 - ERROR - An error occurred while processing WMB-10Xv2-HPF-log2.h5ad: write() argument must be str, not None\n",
+      " 10%|█         | 2/20 [10:53<1:35:25, 318.08s/it]2023-09-23 17:42:16,596 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2\n",
+      "2023-09-23 17:42:18,071 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2/obs\n",
+      "2023-09-23 17:42:19,112 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2/ms/RNA/uns (uns collection)\n",
+      "2023-09-23 17:42:19,937 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2/ms/RNA/var\n",
+      "2023-09-23 17:42:20,133 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:43:32,923 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:43:33,016 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2\n",
+      "2023-09-23 17:43:33,017 - INFO - Successfully converted WMB-10Xv2-CTXsp-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-CTXsp-log2. Progress: 3/10\n",
+      "2023-09-23 17:43:33,024 - ERROR - An error occurred while processing WMB-10Xv2-CTXsp-log2.h5ad: write() argument must be str, not None\n",
+      " 20%|██        | 4/20 [12:09<38:01, 142.62s/it]  2023-09-23 17:43:33,025 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-3-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2\n",
+      "2023-09-23 17:43:35,818 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2/obs\n",
+      "2023-09-23 17:43:36,794 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2/ms/RNA/var\n",
+      "2023-09-23 17:43:36,997 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:44:55,873 - INFO - ...  17.550% done, ETA 6.18 minutes\n",
+      "2023-09-23 17:46:11,964 - INFO - ...  39.655% done, ETA 3.46 minutes\n",
+      "2023-09-23 17:47:19,287 - INFO - ...  60.038% done, ETA 2.26 minutes\n",
+      "2023-09-23 17:48:40,947 - INFO - ...  82.976% done, ETA 57.33 seconds\n",
+      "2023-09-23 17:49:46,561 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:49:46,649 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2\n",
+      "2023-09-23 17:49:46,650 - INFO - Successfully converted WMB-10Xv2-Isocortex-3-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-3-log2. Progress: 4/10\n",
+      "2023-09-23 17:49:46,658 - ERROR - An error occurred while processing WMB-10Xv2-Isocortex-3-log2.h5ad: write() argument must be str, not None\n",
+      " 30%|███       | 6/20 [18:23<38:08, 163.50s/it]2023-09-23 17:49:46,659 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2\n",
+      "2023-09-23 17:49:48,474 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/obs\n",
+      "2023-09-23 17:49:49,944 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/uns (uns collection)\n",
+      "2023-09-23 17:49:50,748 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/var\n",
+      "2023-09-23 17:49:50,947 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:51:20,592 - INFO - ...  46.048% done, ETA 1.75 minutes\n",
+      "2023-09-23 17:52:28,430 - INFO - ...  81.076% done, ETA 36.65 seconds\n",
+      "2023-09-23 17:52:43,992 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:52:44,078 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2\n",
+      "2023-09-23 17:52:44,079 - INFO - Successfully converted WMB-10Xv2-TH-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-TH-log2. Progress: 5/10\n",
+      "2023-09-23 17:52:44,086 - ERROR - An error occurred while processing WMB-10Xv2-TH-log2.h5ad: write() argument must be str, not None\n",
+      " 50%|█████     | 10/20 [21:20<15:50, 95.06s/it]2023-09-23 17:52:44,087 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2\n",
+      "2023-09-23 17:52:45,494 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2/obs\n",
+      "2023-09-23 17:52:46,474 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2/ms/RNA/uns (uns collection)\n",
+      "2023-09-23 17:52:47,295 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2/ms/RNA/var\n",
+      "2023-09-23 17:52:47,492 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:53:29,030 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:53:29,115 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2\n",
+      "2023-09-23 17:53:29,116 - INFO - Successfully converted WMB-10Xv2-MB-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-MB-log2. Progress: 6/10\n",
+      "2023-09-23 17:53:29,122 - ERROR - An error occurred while processing WMB-10Xv2-MB-log2.h5ad: write() argument must be str, not None\n",
+      " 55%|█████▌    | 11/20 [22:05<12:58, 86.54s/it]2023-09-23 17:53:29,124 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2\n",
+      "2023-09-23 17:53:31,794 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2/obs\n",
+      "2023-09-23 17:53:32,752 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2/ms/RNA/var\n",
+      "2023-09-23 17:53:32,960 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2/ms/RNA/X/data\n",
+      "2023-09-23 17:54:49,053 - INFO - ...  16.498% done, ETA 6.42 minutes\n",
+      "2023-09-23 17:55:53,432 - INFO - ...  33.016% done, ETA 4.35 minutes\n",
+      "2023-09-23 17:57:15,414 - INFO - ...  50.770% done, ETA 3.49 minutes\n",
+      "2023-09-23 17:58:20,747 - INFO - ...  65.941% done, ETA 2.44 minutes\n",
+      "2023-09-23 18:00:13,529 - INFO - ...  91.159% done, ETA 37.24 seconds\n",
+      "2023-09-23 18:00:52,757 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:00:52,840 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2\n",
+      "2023-09-23 18:00:52,841 - INFO - Successfully converted WMB-10Xv2-Isocortex-2-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-2-log2. Progress: 7/10\n",
+      "2023-09-23 18:00:52,848 - ERROR - An error occurred while processing WMB-10Xv2-Isocortex-2-log2.h5ad: write() argument must be str, not None\n",
+      " 60%|██████    | 12/20 [29:29<20:51, 156.41s/it]2023-09-23 18:00:52,850 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HY-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2\n",
+      "2023-09-23 18:00:54,500 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2/obs\n",
+      "2023-09-23 18:00:55,753 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2/ms/RNA/uns (uns collection)\n",
+      "2023-09-23 18:00:56,542 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2/ms/RNA/var\n",
+      "2023-09-23 18:00:56,726 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:02:12,798 - INFO - ...  55.127% done, ETA 1.03 minutes\n",
+      "2023-09-23 18:03:03,037 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:03:03,125 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2\n",
+      "2023-09-23 18:03:03,126 - INFO - Successfully converted WMB-10Xv2-HY-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-HY-log2. Progress: 8/10\n",
+      "2023-09-23 18:03:03,133 - ERROR - An error occurred while processing WMB-10Xv2-HY-log2.h5ad: write() argument must be str, not None\n",
+      " 80%|████████  | 16/20 [31:39<06:04, 91.05s/it] 2023-09-23 18:03:03,135 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2\n",
+      "2023-09-23 18:03:05,915 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2/obs\n",
+      "2023-09-23 18:03:06,866 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2/ms/RNA/var\n",
+      "2023-09-23 18:03:07,058 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:04:16,667 - INFO - ...  14.276% done, ETA 6.97 minutes\n",
+      "2023-09-23 18:05:36,965 - INFO - ...  30.172% done, ETA 5.88 minutes\n",
+      "2023-09-23 18:06:57,443 - INFO - ...  48.411% done, ETA 4.08 minutes\n",
+      "2023-09-23 18:08:02,687 - INFO - ...  65.735% done, ETA 2.61 minutes\n",
+      "2023-09-23 18:09:22,399 - INFO - ...  89.549% done, ETA 54.08 seconds\n",
+      "2023-09-23 18:09:58,102 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:09:58,188 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2\n",
+      "2023-09-23 18:09:58,189 - INFO - Successfully converted WMB-10Xv2-Isocortex-4-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-Isocortex-4-log2. Progress: 9/10\n",
+      "2023-09-23 18:09:58,196 - ERROR - An error occurred while processing WMB-10Xv2-Isocortex-4-log2.h5ad: write() argument must be str, not None\n",
+      " 85%|████████▌ | 17/20 [38:34<07:07, 142.44s/it]2023-09-23 18:09:58,197 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-OLF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2\n",
+      "2023-09-23 18:10:00,219 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2/obs\n",
+      "2023-09-23 18:10:02,020 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2/ms/RNA/uns (uns collection)\n",
+      "2023-09-23 18:10:02,878 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2/ms/RNA/var\n",
+      "2023-09-23 18:10:03,085 - INFO - Writing /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:11:11,791 - INFO - ...  25.960% done, ETA 3.27 minutes\n",
+      "2023-09-23 18:12:09,146 - INFO - ...  47.096% done, ETA 2.39 minutes\n",
+      "2023-09-23 18:13:15,204 - INFO - ...  69.914% done, ETA 1.40 minutes\n",
+      "2023-09-23 18:13:48,206 - INFO - ...  90.346% done, ETA 32.63 seconds\n",
+      "2023-09-23 18:14:01,588 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2/ms/RNA/X/data\n",
+      "2023-09-23 18:14:01,677 - INFO - Wrote   /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2\n",
+      "2023-09-23 18:14:01,678 - INFO - Successfully converted WMB-10Xv2-OLF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2-TDB/20230630/WMB-10Xv2-OLF-log2. Progress: 10/10\n",
+      "2023-09-23 18:14:01,685 - ERROR - An error occurred while processing WMB-10Xv2-OLF-log2.h5ad: write() argument must be str, not None\n",
+      "100%|██████████| 20/20 [42:38<00:00, 127.91s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Capture stdout\n",
+    "old_stdout = sys.stdout\n",
+    "new_stdout = io.StringIO()\n",
+    "sys.stdout = new_stdout\n",
+    "\n",
+    "# Run conversion and display progress bar\n",
+    "for filename in tqdm(os.listdir(input_dir)):\n",
+    "    convert_file(filename, file_type=file_type_to_convert)\n",
+    "    \n",
+    "# Restore stdout\n",
+    "sys.stdout = old_stdout\n",
+    "\n",
+    "# Get the captured content and write to file\n",
+    "captured_output = new_stdout.getvalue()\n",
+    "\n",
+    "# Save captured terminal output to a log file\n",
+    "log_file = os.path.join(output_dir, \"conversion_terminal_output.log\")\n",
+    "with open(log_file, 'w') as f:\n",
+    "    f.write(captured_output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5f6884bc-8473-44bd-a92c-0be31c0a7765",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# # Parallel conversion of files\n",
+    "# with ThreadPoolExecutor() as executor:\n",
+    "#     # executor.map(convert_file, os.listdir(input_dir))\n",
+    "#     list(tqdm(executor.map(convert_file, os.listdir(input_dir)), total=len(os.listdir(input_dir))))\n",
+    "# # Save terminal output to log file (if needed in addition to logging)\n",
+    "# log_file = os.path.join(output_dir, \"conversion_terminal_output.log\")\n",
+    "# with open(log_file, 'w') as f:\n",
+    "#     f.write(tiledbsoma.logging.info())"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "TDB",
+   "language": "python",
+   "name": "tdb"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/convert_WMB-10Xv3_to_TDBsoma.ipynb b/notebooks/convert_WMB-10Xv3_to_TDBsoma.ipynb
new file mode 100644
index 00000000..7b83af83
--- /dev/null
+++ b/notebooks/convert_WMB-10Xv3_to_TDBsoma.ipynb
@@ -0,0 +1,487 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2e7673d3-ed4f-40f0-b64b-b46afe453922",
+   "metadata": {},
+   "source": [
+    "# Code for converting H5AD files to TDB\n",
+    "### At the beginning of this file, please indicate whether you want to convert raw or log2 files to TDB.\n",
+    "### At the end of this file, the terminal output is saved to a log file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ec3a2555-9a3f-4765-a53f-744cedb4e86f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Specify the file type to convert: 'both', 'raw', or 'log2'\n",
+    "file_type_to_convert = 'log2' #'both'  or 'raw' or 'log2'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17687871-bbc3-4735-8d7e-77eafd15f3cc",
+   "metadata": {},
+   "source": [
+    "## Preliminary Steps\n",
+    "Import Libraries: Necessary Python packages like anndata, tiledb, logging, etc., are imported.\n",
+    "Print Versions: TileDB versions are printed for debugging and traceability.\n",
+    "Specify Directories: input_dir and output_dir are specified.\n",
+    "List Files: All files in the input_dir are printed for a visual display."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2cbc13a0-af5f-4f8e-a609-f9e7b5c837c6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Import libraries\n",
+    "import logging\n",
+    "import io\n",
+    "import sys\n",
+    "import os\n",
+    "import numpy as np\n",
+    "import anndata as ad\n",
+    "import pandas as pd\n",
+    "import tiledb\n",
+    "import tiledbsoma\n",
+    "import tiledbsoma.io\n",
+    "import tiledbsoma.logging\n",
+    "import logging\n",
+    "# from concurrent.futures import ThreadPoolExecutor # For later for parallel conversion\n",
+    "from tqdm import tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "78cb8c4d-37d8-43e3-a253-f98a2ed72215",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TileDB core version: (2, 15, 2)\n",
+      "TileDB-Py v(0, 21, 3) TileDB-SOMA v1.2.2\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print versions for debugging and traceability\n",
+    "print(\"TileDB core version: {}\".format(tiledb.libtiledb.version()))\n",
+    "print(f\"\"\"TileDB-Py v{tiledb.version()} TileDB-SOMA v{tiledbsoma.__version__}\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "716a4ec8-65bc-4f00-82d3-ee9ee93b5eea",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Input directory: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630\n",
+      "Output directory: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630\n"
+     ]
+    }
+   ],
+   "source": [
+    "download_base = '/shared/Data/abc_download_root'\n",
+    "# input and output directories\n",
+    "input_dir = download_base + \"/expression_matrices/WMB-10Xv3/20230630\"\n",
+    "output_dir = download_base + \"/expression_matrices/WMB-10Xv3-TDB/20230630\"\n",
+    "print(f\"Input directory: {input_dir}\")\n",
+    "print(f\"Output directory: {output_dir}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "697b1f32-3956-4ce7-bb92-f736e97c7038",
+   "metadata": {},
+   "source": [
+    "## File Listing with Sizes\n",
+    "Initialize Lists: Two lists raw_files and log2_files are initialized to store filenames with sizes.\n",
+    "Check File Sizes: For each file in the input_dir, if it's a raw or log2 file, its size in GB is calculated and stored alongside the filename in the corresponding list."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "84816bc1-b561-4a12-9ec8-56785da81fd0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WMB-10Xv3-PAL-log2.h5ad\n",
+      "WMB-10Xv3-CB-log2.h5ad\n",
+      "WMB-10Xv3-OLF-log2.h5ad\n",
+      "WMB-10Xv3-HY-log2.h5ad\n",
+      "WMB-10Xv3-STR-log2.h5ad\n",
+      "WMB-10Xv3-Isocortex-2-log2.h5ad\n",
+      "WMB-10Xv3-MB-log2.h5ad\n",
+      "WMB-10Xv3-HPF-log2.h5ad\n",
+      "WMB-10Xv3-Isocortex-1-log2.h5ad\n",
+      "WMB-10Xv3-MY-log2.h5ad\n",
+      "WMB-10Xv3-CTXsp-log2.h5ad\n",
+      "WMB-10Xv3-P-log2.h5ad\n",
+      "WMB-10Xv3-TH-log2.h5ad\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get a list of files for visual display\n",
+    "for filename in (os.listdir(input_dir)):\n",
+    "    print(filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7196ea8f-7154-40c4-aa99-6776e141e5bc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Raw Files                                         Log2 Files                                        \n",
+      "====================================================================================================\n",
+      "                                                  WMB-10Xv3-PAL-log2.h5ad (3.79 GB)                 \n",
+      "                                                  WMB-10Xv3-CB-log2.h5ad (5.23 GB)                  \n",
+      "                                                  WMB-10Xv3-OLF-log2.h5ad (2.90 GB)                 \n",
+      "                                                  WMB-10Xv3-HY-log2.h5ad (6.75 GB)                  \n",
+      "                                                  WMB-10Xv3-STR-log2.h5ad (11.10 GB)                \n",
+      "                                                  WMB-10Xv3-Isocortex-2-log2.h5ad (7.78 GB)         \n",
+      "                                                  WMB-10Xv3-MB-log2.h5ad (12.78 GB)                 \n",
+      "                                                  WMB-10Xv3-HPF-log2.h5ad (6.90 GB)                 \n",
+      "                                                  WMB-10Xv3-Isocortex-1-log2.h5ad (10.96 GB)        \n",
+      "                                                  WMB-10Xv3-MY-log2.h5ad (6.71 GB)                  \n",
+      "                                                  WMB-10Xv3-CTXsp-log2.h5ad (3.05 GB)               \n",
+      "                                                  WMB-10Xv3-P-log2.h5ad (4.84 GB)                   \n",
+      "                                                  WMB-10Xv3-TH-log2.h5ad (5.41 GB)                  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize lists to hold filenames and sizes\n",
+    "raw_files = []\n",
+    "log2_files = []\n",
+    "\n",
+    "# Function to get file size in GB\n",
+    "def get_size_in_gb(file_path):\n",
+    "    size_bytes = os.path.getsize(file_path)\n",
+    "    size_gb = size_bytes / (1024 ** 3)\n",
+    "    return f\"{size_gb:.2f} GB\"\n",
+    "\n",
+    "# Get a list of files for visual display\n",
+    "for filename in os.listdir(input_dir):\n",
+    "    full_path = os.path.join(input_dir, filename)\n",
+    "    if filename.endswith(\"raw.h5ad\"):\n",
+    "        size = get_size_in_gb(full_path)\n",
+    "        raw_files.append(f\"{filename} ({size})\")\n",
+    "    elif filename.endswith(\"log2.h5ad\"):\n",
+    "        size = get_size_in_gb(full_path)\n",
+    "        log2_files.append(f\"{filename} ({size})\")\n",
+    "\n",
+    "# Print filenames in two columns: raw and log2\n",
+    "print(f\"{'Raw Files':<50}{'Log2 Files':<50}\")\n",
+    "print(\"=\" * 100)\n",
+    "\n",
+    "# Determine the maximum number of rows to print\n",
+    "max_rows = max(len(raw_files), len(log2_files))\n",
+    "\n",
+    "# Print the filenames and sizes side by side\n",
+    "for i in range(max_rows):\n",
+    "    raw_file = raw_files[i] if i < len(raw_files) else ''\n",
+    "    log2_file = log2_files[i] if i < len(log2_files) else ''\n",
+    "    print(f\"{raw_file:<50}{log2_file:<50}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15baac3c-4f28-4c86-8a95-f8e59a18d326",
+   "metadata": {},
+   "source": [
+    "## Logging Setup\n",
+    "Initialize Logging: Logging is set up to capture messages at the INFO level.\n",
+    "Log File: A conversion_all.log file is created in a conversionLog directory under output_dir. This file will capture all the logging messages."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "dcc16889-7963-42eb-b4a2-07a656f6e027",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2023-09-23 18:33:34,610 - INFO - Starting conversion...\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize logging\n",
+    "conversion_log_dir = os.path.join(output_dir, \"conversionLog\")\n",
+    "\n",
+    "# Create the conversionLog directory if it doesn't exist\n",
+    "if not os.path.exists(conversion_log_dir):\n",
+    "    os.makedirs(conversion_log_dir)\n",
+    "\n",
+    "# Setup Python logging\n",
+    "logging.basicConfig(level=logging.INFO,\n",
+    "                    format='%(asctime)s - %(levelname)s - %(message)s',\n",
+    "                    handlers=[logging.FileHandler(os.path.join(conversion_log_dir, 'conversion_all.log'), 'w', 'utf-8'),\n",
+    "                              logging.StreamHandler()])\n",
+    "\n",
+    "logging.info(\"Starting conversion...\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b61a80ab-1432-44b8-a207-921079c8d4dd",
+   "metadata": {},
+   "source": [
+    "Counters Initialization\n",
+    "Initialize Counters: Counters for completed_files and total_files are initialized to keep track of conversion progress."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "22e3a2a0-c021-4dac-951b-e7be9af4722f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Initialize counters for completed files and total files\n",
+    "completed_files = {'raw': 0, 'log2': 0}\n",
+    "total_files = {'raw': len([f for f in os.listdir(input_dir) if f.endswith(\"raw.h5ad\")]),\n",
+    "               'log2': len([f for f in os.listdir(input_dir) if f.endswith(\"log2.h5ad\")])}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1eac6875-9a05-4e35-a1e4-023d55d63552",
+   "metadata": {},
+   "source": [
+    "## The Conversion Function (convert_file)\n",
+    "File Type Check: Validates the file_type argument and logs an error if invalid.\n",
+    "Conversion: Checks if the file should be converted based on its suffix and the file_type argument.\n",
+    "Buffer Size: Dynamically sets the TileDB buffer size based on the size of the AnnData object.\n",
+    "Column Check: Checks for and removes columns with non-ASCII characters in the AnnData object.\n",
+    "TileDB Conversion: Calls tiledbsoma.io.from_anndata() to convert the AnnData object to a TileDB array.\n",
+    "Progress Logging: Logs the conversion progress to both the terminal and the conversion_all.log file.\n",
+    "TileDB Logging: Captures TileDB-specific logging into individual log files, one for each converted file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4b8c2dfb-54c1-4fdf-a7eb-9cb84a6e772a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Function to convert a single file\n",
+    "def convert_file(filename, file_type='both'):\n",
+    "    try:\n",
+    "        if file_type not in ['both', 'raw', 'log2']:\n",
+    "            logging.error(\"Invalid file_type. Use 'both', 'raw', or 'log2'\")\n",
+    "            return\n",
+    "        \n",
+    "        if (filename.endswith(\"raw.h5ad\") and file_type in ['both', 'raw']) or \\\n",
+    "           (filename.endswith(\"log2.h5ad\") and file_type in ['both', 'log2']):\n",
+    "            \n",
+    "            key = 'raw' if filename.endswith(\"raw.h5ad\") else 'log2'\n",
+    "            \n",
+    "            fname = os.path.join(input_dir, filename)\n",
+    "            uri = os.path.join(output_dir, os.path.splitext(filename)[0])\n",
+    "\n",
+    "            logging.info(f\"Starting conversion: {fname} to {uri}\")\n",
+    "\n",
+    "            if os.path.exists(uri):\n",
+    "                logging.info(f\"Output file {uri} already exists. Skipping.\")\n",
+    "                return\n",
+    "\n",
+    "            adata = ad.read_h5ad(fname, 'r')\n",
+    "\n",
+    "            # Update buffer size dynamically based on the AnnData object size\n",
+    "            # Calculate the size of the AnnData object's X attribute in bytes\n",
+    "            adata_nbytes = adata.X.nbytes if hasattr(adata.X, 'nbytes') else 0\n",
+    "            # Calculate the dynamic buffer size\n",
+    "            buffer_size = min(50 * 1024**2, adata_nbytes * 2)\n",
+    "            # Update the config with the new buffer size\n",
+    "            cfg = tiledb.Ctx().config()\n",
+    "            cfg.update({'py.init_buffer_bytes': buffer_size})\n",
+    "\n",
+    "            for col in adata.obs.select_dtypes(include=[pd.CategoricalDtype]).columns:\n",
+    "                if adata.obs[col].str.contains(r'[^\\x00-\\x7F]+').any():\n",
+    "                    logging.warning(f\"Column '{col}' in file {filename} contains records with non-ASCII characters. Removing column.\")\n",
+    "                    adata.obs.drop(col, axis=1, inplace=True)\n",
+    "\n",
+    "            tiledbsoma.io.from_anndata(uri, adata, measurement_name=\"RNA\")\n",
+    "            \n",
+    "            # Increment and display the counter\n",
+    "            completed_files[key] += 1\n",
+    "            logging.info(f\"Successfully converted {filename} to {uri}. Progress: {completed_files[key]}/{total_files[key]}\")\n",
+    "\n",
+    "            # Save tiledb-specific logging output to individual log file\n",
+    "            # log_file = os.path.join(conversion_log_dir, f\"{os.path.splitext(filename)[0]}.log\")\n",
+    "            # with open(log_file, 'w') as f:\n",
+    "            #     f.write(tiledbsoma.logging.info())   # currently spits out an error since the value returned by tiledbsoma.logging.info() is None             \n",
+    "                \n",
+    "    except Exception as e:\n",
+    "        logging.error(f\"An error occurred while processing {filename}: {e}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "916c28f0-fd53-4dbb-9137-6a19c3fd2ce1",
+   "metadata": {},
+   "source": [
+    "## Run &Capturing Terminal Output\n",
+    "Capture stdout: The standard output is captured into a StringIO object.\n",
+    "Run Conversion: The convert_file function is called for each file in the input_dir while displaying a progress bar.\n",
+    "Restore stdout: The standard output is restored.\n",
+    "Save Captured Output: The captured terminal output is saved into a log file named conversion_terminal_output.log in the output_dir.\n",
+    "### Output & Logging\n",
+    "Terminal: You will see logging messages and a progress bar.\n",
+    "conversion_all.log: This file will contain all the logging messages.\n",
+    "Individual Log Files: TileDB-specific logging for each file will be saved in individual .log files in the conversionLog directory.\n",
+    "conversion_terminal_output.log: This will contain everything that was printed to the terminal."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c5af70bf-9979-402e-bf71-e8c3128b3721",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/13 [00:00<?, ?it/s]2023-09-23 18:33:34,854 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-PAL-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-PAL-log2\n",
+      "2023-09-23 18:37:08,642 - INFO - Successfully converted WMB-10Xv3-PAL-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-PAL-log2. Progress: 1/13\n",
+      "  8%|▊         | 1/13 [03:33<42:45, 213.79s/it]2023-09-23 18:37:08,647 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CB-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-CB-log2\n",
+      "2023-09-23 18:41:30,332 - INFO - Successfully converted WMB-10Xv3-CB-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-CB-log2. Progress: 2/13\n",
+      " 15%|█▌        | 2/13 [07:55<44:21, 241.97s/it]2023-09-23 18:41:30,336 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-OLF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-OLF-log2\n",
+      "2023-09-23 18:43:56,218 - INFO - Successfully converted WMB-10Xv3-OLF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-OLF-log2. Progress: 3/13\n",
+      " 23%|██▎       | 3/13 [10:21<33:00, 198.09s/it]2023-09-23 18:43:56,222 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HY-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-HY-log2\n",
+      "2023-09-23 18:49:39,187 - INFO - Successfully converted WMB-10Xv3-HY-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-HY-log2. Progress: 4/13\n",
+      " 31%|███       | 4/13 [16:04<38:17, 255.29s/it]2023-09-23 18:49:39,188 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-STR-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-STR-log2\n",
+      "2023-09-23 18:59:20,902 - INFO - Successfully converted WMB-10Xv3-STR-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-STR-log2. Progress: 5/13\n",
+      " 38%|███▊      | 5/13 [25:46<49:44, 373.00s/it]2023-09-23 18:59:20,905 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-2-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-Isocortex-2-log2\n",
+      "2023-09-23 19:05:52,093 - INFO - Successfully converted WMB-10Xv3-Isocortex-2-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-Isocortex-2-log2. Progress: 6/13\n",
+      " 46%|████▌     | 6/13 [32:17<44:14, 379.19s/it]2023-09-23 19:05:52,095 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MB-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-MB-log2\n",
+      "2023-09-23 19:17:03,638 - INFO - Successfully converted WMB-10Xv3-MB-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-MB-log2. Progress: 7/13\n",
+      " 54%|█████▍    | 7/13 [43:28<47:28, 474.76s/it]2023-09-23 19:17:03,641 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HPF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-HPF-log2\n",
+      "2023-09-23 19:23:01,416 - INFO - Successfully converted WMB-10Xv3-HPF-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-HPF-log2. Progress: 8/13\n",
+      " 62%|██████▏   | 8/13 [49:26<36:27, 437.52s/it]2023-09-23 19:23:01,419 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-1-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-Isocortex-1-log2\n",
+      "2023-09-23 19:32:34,751 - INFO - Successfully converted WMB-10Xv3-Isocortex-1-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-Isocortex-1-log2. Progress: 9/13\n",
+      " 69%|██████▉   | 9/13 [58:59<31:59, 479.98s/it]2023-09-23 19:32:34,753 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MY-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-MY-log2\n",
+      "2023-09-23 19:38:38,825 - INFO - Successfully converted WMB-10Xv3-MY-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-MY-log2. Progress: 10/13\n",
+      " 77%|███████▋  | 10/13 [1:05:03<22:12, 444.20s/it]2023-09-23 19:38:38,828 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CTXsp-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-CTXsp-log2\n",
+      "2023-09-23 19:41:29,428 - INFO - Successfully converted WMB-10Xv3-CTXsp-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-CTXsp-log2. Progress: 11/13\n",
+      " 85%|████████▍ | 11/13 [1:07:54<12:00, 360.46s/it]2023-09-23 19:41:29,431 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-P-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-P-log2\n",
+      "2023-09-23 19:45:36,719 - INFO - Successfully converted WMB-10Xv3-P-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-P-log2. Progress: 12/13\n",
+      " 92%|█████████▏| 12/13 [1:12:01<05:26, 326.03s/it]2023-09-23 19:45:36,721 - INFO - Starting conversion: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-TH-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-TH-log2\n",
+      "2023-09-23 19:50:40,653 - INFO - Successfully converted WMB-10Xv3-TH-log2.h5ad to /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3-TDB/20230630/WMB-10Xv3-TH-log2. Progress: 13/13\n",
+      "100%|██████████| 13/13 [1:17:05<00:00, 355.83s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Capture stdout\n",
+    "old_stdout = sys.stdout\n",
+    "new_stdout = io.StringIO()\n",
+    "sys.stdout = new_stdout\n",
+    "\n",
+    "# Run conversion and display progress bar\n",
+    "for filename in tqdm(os.listdir(input_dir)):\n",
+    "    convert_file(filename, file_type=file_type_to_convert)\n",
+    "    \n",
+    "# Restore stdout\n",
+    "sys.stdout = old_stdout\n",
+    "\n",
+    "# Get the captured content and write to file\n",
+    "captured_output = new_stdout.getvalue()\n",
+    "\n",
+    "# Save captured terminal output to a log file\n",
+    "log_file = os.path.join(output_dir, \"conversion_terminal_output.log\")\n",
+    "with open(log_file, 'w') as f:\n",
+    "    f.write(captured_output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5f6884bc-8473-44bd-a92c-0be31c0a7765",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# # Parallel conversion of files\n",
+    "# with ThreadPoolExecutor() as executor:\n",
+    "#     # executor.map(convert_file, os.listdir(input_dir))\n",
+    "#     list(tqdm(executor.map(convert_file, os.listdir(input_dir)), total=len(os.listdir(input_dir))))\n",
+    "# # Save terminal output to log file (if needed in addition to logging)\n",
+    "# log_file = os.path.join(output_dir, \"conversion_terminal_output.log\")\n",
+    "# with open(log_file, 'w') as f:\n",
+    "#     f.write(tiledbsoma.logging.info())"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "TDB",
+   "language": "python",
+   "name": "tdb"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/downloadBaseFiles.ipynb b/notebooks/downloadBaseFiles.ipynb
new file mode 100644
index 00000000..78a8bc13
--- /dev/null
+++ b/notebooks/downloadBaseFiles.ipynb
@@ -0,0 +1,1221 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0fc2688d-d344-4f47-a0c2-e46906c838f4",
+   "metadata": {},
+   "source": [
+    "# Importing libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "0d9d69bb-176b-4e8f-ab99-5771a16dc74d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "import json\n",
+    "import os\n",
+    "import pathlib\n",
+    "import subprocess\n",
+    "import time\n",
+    "from tqdm import tqdm  # Importing the tqdm library"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b3956a6b-6f71-40d6-929f-095bcda5c6e3",
+   "metadata": {},
+   "source": [
+    "### Start by downloading the manifest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c1a218b6-35c2-4dbe-a203-b273f0ed53db",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "version:  20230830\n"
+     ]
+    }
+   ],
+   "source": [
+    "version = '20230830'\n",
+    "url = 'https://allen-brain-cell-atlas.s3-us-west-2.amazonaws.com/releases/%s/manifest.json' % version\n",
+    "manifest = json.loads(requests.get(url).text)\n",
+    "print(\"version: \", manifest['version'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c7fcf285-a5a9-4dd1-b5a2-09a4862a2d9f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "version: 20230830\n",
+      "resource_uri: s3://allen-brain-cell-atlas/\n"
+     ]
+    }
+   ],
+   "source": [
+    "manifest.keys()\n",
+    "print(\"version:\",manifest['version'])\n",
+    "print(\"resource_uri:\",manifest['resource_uri'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4dee56bf-150e-43df-a812-12ed64a471dc",
+   "metadata": {},
+   "source": [
+    "Get the size of the manifest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "8c43c5aa-7654-494b-a447-5e5561ac796b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "expression_matrices/MERFISH-C57BL6J-638850/20230830 : 14.21 GB\n",
+      "metadata/MERFISH-C57BL6J-638850/20230830 : 1.81 GB\n",
+      "expression_matrices/MERFISH-C57BL6J-638850-sections/20230630 : 14.31 GB\n",
+      "expression_matrices/WMB-10Xv2/20230630 : 104.16 GB\n",
+      "expression_matrices/WMB-10Xv3/20230630 : 176.41 GB\n",
+      "expression_matrices/WMB-10XMulti/20230830 : 0.21 GB\n",
+      "metadata/WMB-10X/20230830 : 2.39 GB\n",
+      "metadata/WMB-taxonomy/20230830 : 0.01 GB\n",
+      "metadata/WMB-neighborhoods/20230830 : 3.00 GB\n",
+      "image_volumes/Allen-CCF-2020/20230630 : 0.37 GB\n",
+      "metadata/Allen-CCF-2020/20230630 : 0.00 GB\n",
+      "image_volumes/MERFISH-C57BL6J-638850-CCF/20230630 : 0.11 GB\n",
+      "metadata/MERFISH-C57BL6J-638850-CCF/20230830 : 2.01 GB\n",
+      "expression_matrices/Zhuang-ABCA-1/20230830 : 3.09 GB\n",
+      "metadata/Zhuang-ABCA-1/20230830 : 1.33 GB\n",
+      "metadata/Zhuang-ABCA-1-CCF/20230830 : 0.21 GB\n",
+      "expression_matrices/Zhuang-ABCA-2/20230830 : 1.30 GB\n",
+      "metadata/Zhuang-ABCA-2/20230830 : 0.57 GB\n",
+      "metadata/Zhuang-ABCA-2-CCF/20230830 : 0.08 GB\n",
+      "expression_matrices/Zhuang-ABCA-3/20230830 : 1.69 GB\n",
+      "metadata/Zhuang-ABCA-3/20230830 : 0.74 GB\n",
+      "metadata/Zhuang-ABCA-3-CCF/20230830 : 0.12 GB\n",
+      "expression_matrices/Zhuang-ABCA-4/20230830 : 0.16 GB\n",
+      "metadata/Zhuang-ABCA-4/20230830 : 0.08 GB\n",
+      "metadata/Zhuang-ABCA-4-CCF/20230830 : 0.01 GB\n"
+     ]
+    }
+   ],
+   "source": [
+    "GB = float(float(1024) ** 3)\n",
+    "\n",
+    "for r in manifest['directory_listing'] :    \n",
+    "    r_dict =  manifest['directory_listing'][r]\n",
+    "    for d in r_dict['directories'] :\n",
+    "        d_dict = r_dict['directories'][d]        \n",
+    "        print(d_dict['relative_path'],\":\",'%0.2f GB' % (d_dict['total_size']/GB))\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4f6e29b8-7913-422a-90e9-a73db47ba309",
+   "metadata": {},
+   "source": [
+    "Set the download base"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "34c3b596-ba8c-49bc-929b-59fde54ebea6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "download_base = '/shared/Data/abc_download_root'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ca48e56f-a8d6-43dd-a9c6-f58aaa4d81fe",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def download_file( file_dict ) :\n",
+    "    \n",
+    "    print(file_dict['relative_path'],file_dict['size'])\n",
+    "    local_path = os.path.join( download_base, file_dict['relative_path'] )\n",
+    "    local_path = pathlib.Path( local_path )\n",
+    "    remote_path = manifest['resource_uri'] + file_dict['relative_path']\n",
+    "\n",
+    "    command = \"aws s3 cp --no-sign-request %s %s\" % (remote_path, local_path)\n",
+    "    print(command)\n",
+    "\n",
+    "    start = time.process_time()\n",
+    "    # Uncomment to download file\n",
+    "    result = subprocess.run(command.split(' '),stdout=subprocess.PIPE)\n",
+    "    print(\"time taken: \", time.process_time() - start)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e48a69cc-ff59-4bc4-9a5b-697db7588d5e",
+   "metadata": {},
+   "source": [
+    "## Download individual files from WMB-10Xv2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "be83f02a-4b32-4320-b9fc-4c7b2e6eeb29",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 4038679930\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad 4038679930\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n",
+      "time taken:  0.09134629800000016\n"
+     ]
+    }
+   ],
+   "source": [
+    "expression_matrices = manifest['file_listing']['WMB-10Xv2']['expression_matrices']\n",
+    "file_dict = expression_matrices['WMB-10Xv2-TH']['log2']['files']['h5ad']\n",
+    "print('size:',file_dict['size'])\n",
+    "download_file( file_dict )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "ae616f0e-138e-49b5-b2bf-1d63cc0f7e39",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 4038679930\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad 4038679930\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad\n",
+      "time taken:  0.09228066099999999\n"
+     ]
+    }
+   ],
+   "source": [
+    "expression_matrices = manifest['file_listing']['WMB-10Xv2']['expression_matrices']\n",
+    "file_dict = expression_matrices['WMB-10Xv2-TH']['raw']['files']['h5ad']\n",
+    "print('size:',file_dict['size'])\n",
+    "download_file( file_dict )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a31d4a9-4c6d-4ff5-acca-5f7bd65c623c",
+   "metadata": {},
+   "source": [
+    "Download individual files from WMB-10XMulti"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "860b27ed-7279-4269-91d4-4f01b81c8fe7",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 89318511\n",
+      "expression_matrices/WMB-10XMulti/20230830/WMB-10XMulti-log2.h5ad 89318511\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10XMulti/20230830/WMB-10XMulti-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10XMulti/20230830/WMB-10XMulti-log2.h5ad\n",
+      "time taken:  0.0051590729999999585\n"
+     ]
+    }
+   ],
+   "source": [
+    "datasets = ['WMB-10XMulti']\n",
+    "for d in datasets :\n",
+    "    expression_matrices = manifest['file_listing'][d]['expression_matrices']\n",
+    "    file_dict = expression_matrices[d]['log2']['files']['h5ad']\n",
+    "    print('size:',file_dict['size'])\n",
+    "    download_file( file_dict )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a6d60b97-6d0c-45ae-8db0-350c9533fa3d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 132220015\n",
+      "expression_matrices/WMB-10XMulti/20230830/WMB-10XMulti-raw.h5ad 132220015\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10XMulti/20230830/WMB-10XMulti-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10XMulti/20230830/WMB-10XMulti-raw.h5ad\n",
+      "time taken:  0.0059165059999999325\n"
+     ]
+    }
+   ],
+   "source": [
+    "datasets = ['WMB-10XMulti']\n",
+    "for d in datasets :\n",
+    "    expression_matrices = manifest['file_listing'][d]['expression_matrices']\n",
+    "    file_dict = expression_matrices[d]['raw']['files']['h5ad']\n",
+    "    print('size:',file_dict['size'])\n",
+    "    download_file( file_dict )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e5a5e54f-59e5-49de-9e71-a5a5d8c3dbca",
+   "metadata": {},
+   "source": [
+    "Get the list of files in the WMB-10Xv2 directory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "b42de275-af00-4eef-a2c5-2315d1a5d8d9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WMB-10Xv2-Isocortex-2\n",
+      "WMB-10Xv2-MB\n",
+      "WMB-10Xv2-TH\n",
+      "WMB-10Xv2-CTXsp\n",
+      "WMB-10Xv2-Isocortex-4\n",
+      "WMB-10Xv2-HY\n",
+      "WMB-10Xv2-OLF\n",
+      "WMB-10Xv2-Isocortex-3\n",
+      "WMB-10Xv2-Isocortex-1\n",
+      "WMB-10Xv2-HPF\n"
+     ]
+    }
+   ],
+   "source": [
+    "expression_matrices = manifest['file_listing']['WMB-10Xv2']['expression_matrices']\n",
+    "for file_dict in expression_matrices :\n",
+    "    # print('size:',file_dict['size'])\n",
+    "    print( file_dict )\n",
+    "\n",
+    "# file_dict = expression_matrices['WMB-10Xv2-TH']['raw']['files']['h5ad']\n",
+    "# print('size:',file_dict['size'])\n",
+    "# download_file( file_dict )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "2a3dff5b-5079-4d4b-a052-32f9cf20b1aa",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/image_volumes/Allen-CCF-2020/20230630 /shared/Data/abc_download_root/image_volumes/Allen-CCF-2020/20230630\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/image_volumes/MERFISH-C57BL6J-638850-CCF/20230630 /shared/Data/abc_download_root/image_volumes/MERFISH-C57BL6J-638850-CCF/20230630\n"
+     ]
+    }
+   ],
+   "source": [
+    "for r in manifest['directory_listing'] :\n",
+    "    \n",
+    "    r_dict =  manifest['directory_listing'][r]\n",
+    "    # print(r_dict)\n",
+    "    for d in r_dict['directories'] :\n",
+    "        \n",
+    "        if d != 'image_volumes' :\n",
+    "            continue\n",
+    "        d_dict = r_dict['directories'][d]\n",
+    "        local_path = os.path.join( download_base, d_dict['relative_path'])\n",
+    "        local_path = pathlib.Path( local_path )\n",
+    "        remote_path = manifest['resource_uri'] + d_dict['relative_path']\n",
+    "        \n",
+    "        command = \"aws s3 sync --no-sign-request %s %s\" % (remote_path, local_path)\n",
+    "        print(command)\n",
+    "        \n",
+    "        start = time.process_time()\n",
+    "        # Uncomment to download directories\n",
+    "        # result = subprocess.run(command.split(),stdout=subprocess.PIPE)\n",
+    "        # print(\"time taken: \", time.process_time() - start)\n",
+    "  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "05db7307-123f-49d4-911f-1f3feb1d9ea8",
+   "metadata": {},
+   "source": [
+    "## Download individual files from WMB-10Xv2 [log2 file]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3d10b8b8-892c-4a24-8bde-b18c21de03f2",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "First let's see what is in the manifest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "d39f19f2-d67a-4498-92e6-f386c57bb31d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "expression_matrices\n",
+      "{'version': '20230830', 'relative_path': 'expression_matrices/MERFISH-C57BL6J-638850/20230830', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/MERFISH-C57BL6J-638850/20230830/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/MERFISH-C57BL6J-638850/20230830/', 'total_size': 15255179148}\n",
+      "expression_matrices\n",
+      "{'version': '20230630', 'relative_path': 'expression_matrices/MERFISH-C57BL6J-638850-sections/20230630', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/MERFISH-C57BL6J-638850-sections/20230630/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/MERFISH-C57BL6J-638850-sections/20230630/', 'total_size': 15363706998}\n",
+      "expression_matrices\n",
+      "{'version': '20230630', 'relative_path': 'expression_matrices/WMB-10Xv2/20230630', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/WMB-10Xv2/20230630/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/WMB-10Xv2/20230630/', 'total_size': 111838076296}\n",
+      "expression_matrices\n",
+      "{'version': '20230630', 'relative_path': 'expression_matrices/WMB-10Xv3/20230630', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/WMB-10Xv3/20230630/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/WMB-10Xv3/20230630/', 'total_size': 189424020276}\n",
+      "expression_matrices\n",
+      "{'version': '20230830', 'relative_path': 'expression_matrices/WMB-10XMulti/20230830', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/WMB-10XMulti/20230830/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/WMB-10XMulti/20230830/', 'total_size': 221538526}\n",
+      "expression_matrices\n",
+      "{'version': '20230830', 'relative_path': 'expression_matrices/Zhuang-ABCA-1/20230830', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/Zhuang-ABCA-1/20230830/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/Zhuang-ABCA-1/20230830/', 'total_size': 3321931046}\n",
+      "expression_matrices\n",
+      "{'version': '20230830', 'relative_path': 'expression_matrices/Zhuang-ABCA-2/20230830', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/Zhuang-ABCA-2/20230830/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/Zhuang-ABCA-2/20230830/', 'total_size': 1391805481}\n",
+      "expression_matrices\n",
+      "{'version': '20230830', 'relative_path': 'expression_matrices/Zhuang-ABCA-3/20230830', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/Zhuang-ABCA-3/20230830/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/Zhuang-ABCA-3/20230830/', 'total_size': 1818891831}\n",
+      "expression_matrices\n",
+      "{'version': '20230830', 'relative_path': 'expression_matrices/Zhuang-ABCA-4/20230830', 'url': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/expression_matrices/Zhuang-ABCA-4/20230830/', 'view_link': 'https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html#expression_matrices/Zhuang-ABCA-4/20230830/', 'total_size': 170987244}\n"
+     ]
+    }
+   ],
+   "source": [
+    "for r in manifest['directory_listing'] :    \n",
+    "    r_dict =  manifest['directory_listing'][r]\n",
+    "    for d in r_dict['directories'] :\n",
+    "        if d != 'expression_matrices' :\n",
+    "            continue\n",
+    "        print(d)\n",
+    "        d_dict = r_dict['directories'][d]   \n",
+    "        # if d_dict != 'WMB-10Xv2' :\n",
+    "        #     continue\n",
+    "        print(d_dict)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ec0d7686-558b-4f04-93bc-39b2d326b2d8",
+   "metadata": {},
+   "source": [
+    "### Download individual files from WMB-10Xv2 [log2 file]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c9c7fd77-e6d3-45b0-a5e4-a5a88c1af4ad",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:   0%|          | 0/10 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 9444387082\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-log2.h5ad 9444387082\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  10%|█         | 1/10 [01:55<17:15, 115.00s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.20598851000000007\n",
+      "size: 817433734\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-log2.h5ad 817433734\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  20%|██        | 2/10 [02:07<07:17, 54.68s/it] "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.025496951999999906\n",
+      "size: 4038679930\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad 4038679930\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  30%|███       | 3/10 [03:06<06:36, 56.70s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.095607628\n",
+      "size: 1740441622\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-log2.h5ad 1740441622\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  40%|████      | 4/10 [03:32<04:27, 44.52s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.04063343400000008\n",
+      "size: 8692589466\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-log2.h5ad 8692589466\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-log2.h5ad\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize the dictionary\n",
+    "expression_matrices = manifest['file_listing']['WMB-10Xv2']['expression_matrices']\n",
+    "\n",
+    "# Initialize the tqdm progress bar\n",
+    "categories = list(expression_matrices.keys())\n",
+    "with tqdm(total=len(categories), desc=\"Downloading Files\") as pbar:\n",
+    "\n",
+    "    # Iterate over the keys, which represent different categories\n",
+    "    for category in categories:\n",
+    "        \n",
+    "        # Look for 'log2' key in each category dictionary\n",
+    "        if 'log2' in expression_matrices[category]:\n",
+    "            \n",
+    "            # Get the 'files' dictionary under 'log2'\n",
+    "            files_dict = expression_matrices[category]['log2']['files']\n",
+    "            \n",
+    "            # Check if 'h5ad' format files are present\n",
+    "            if 'h5ad' in files_dict:\n",
+    "                file_dict = files_dict['h5ad']\n",
+    "                \n",
+    "                # Prepare the local and remote paths for downloading\n",
+    "                local_path = os.path.join(download_base, file_dict['relative_path'])\n",
+    "                local_path = pathlib.Path(local_path)\n",
+    "                remote_path = manifest['resource_uri'] + file_dict['relative_path']\n",
+    "                \n",
+    "                # Print size and paths before downloading\n",
+    "                print('size:', file_dict['size'])\n",
+    "                print('Local Path:', local_path)\n",
+    "                print('Remote Path:', remote_path)\n",
+    "                \n",
+    "                # Download the file using your existing download_file function\n",
+    "                # Or you could directly insert the AWS S3 command here\n",
+    "                download_file(file_dict)\n",
+    "        \n",
+    "        # Update the progress bar\n",
+    "        pbar.update(1)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e1586f47-7e1b-4bea-ac4f-d5735354578b",
+   "metadata": {},
+   "source": [
+    "### Now download individual files from WMB-10Xv2 [raw file]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "cbe2b087-a25b-4227-bf3d-1a999c912be6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:   0%|          | 0/10 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 9444387082\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-raw.h5ad 9444387082\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-2-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  10%|█         | 1/10 [01:52<16:48, 112.10s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.20220492899999987\n",
+      "size: 811153174\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-raw.h5ad 811153174\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-MB-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  20%|██        | 2/10 [02:03<07:03, 52.99s/it] "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.020529559999999947\n",
+      "size: 4038679930\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad 4038679930\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  30%|███       | 3/10 [03:01<06:25, 55.07s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.0947930530000003\n",
+      "size: 1734161062\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-raw.h5ad 1734161062\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-CTXsp-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  40%|████      | 4/10 [03:25<04:18, 43.06s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.042439166999999944\n",
+      "size: 8692589466\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-raw.h5ad 8692589466\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-4-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  50%|█████     | 5/10 [05:14<05:33, 66.71s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.1759996639999999\n",
+      "size: 2908443982\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HY-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HY-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HY-raw.h5ad 2908443982\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HY-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HY-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  60%|██████    | 6/10 [05:55<03:52, 58.11s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.06767890900000006\n",
+      "size: 5128120156\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-OLF-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-OLF-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-OLF-raw.h5ad 5128120156\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-OLF-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-OLF-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  70%|███████   | 7/10 [07:09<03:09, 63.16s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.11671811900000018\n",
+      "size: 8457819034\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-3-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-3-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-3-raw.h5ad 8457819034\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-3-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-3-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  80%|████████  | 8/10 [08:54<02:32, 76.43s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.18850982699999985\n",
+      "size: 8601133978\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-1-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-1-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-1-raw.h5ad 8601133978\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-1-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-Isocortex-1-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  90%|█████████ | 9/10 [10:41<01:26, 86.01s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.19585635299999993\n",
+      "size: 6096269724\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HPF-raw.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HPF-raw.h5ad\n",
+      "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HPF-raw.h5ad 6096269724\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HPF-raw.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-HPF-raw.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files: 100%|██████████| 10/10 [12:01<00:00, 72.11s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.13518696200000013\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize the dictionary\n",
+    "expression_matrices = manifest['file_listing']['WMB-10Xv2']['expression_matrices']\n",
+    "\n",
+    "# Initialize the tqdm progress bar\n",
+    "categories = list(expression_matrices.keys())\n",
+    "with tqdm(total=len(categories), desc=\"Downloading Files\") as pbar:\n",
+    "\n",
+    "    # Iterate over the keys, which represent different categories\n",
+    "    for category in categories:\n",
+    "        \n",
+    "        # Look for 'raw' key in each category dictionary\n",
+    "        if 'raw' in expression_matrices[category]:\n",
+    "            \n",
+    "            # Get the 'files' dictionary under 'raw'\n",
+    "            files_dict = expression_matrices[category]['raw']['files']\n",
+    "            \n",
+    "            # Check if 'h5ad' format files are present\n",
+    "            if 'h5ad' in files_dict:\n",
+    "                file_dict = files_dict['h5ad']\n",
+    "                \n",
+    "                # Prepare the local and remote paths for downloading\n",
+    "                local_path = os.path.join(download_base, file_dict['relative_path'])\n",
+    "                local_path = pathlib.Path(local_path)\n",
+    "                remote_path = manifest['resource_uri'] + file_dict['relative_path']\n",
+    "                \n",
+    "                # Print size and paths before downloading\n",
+    "                print('size:', file_dict['size'])\n",
+    "                print('Local Path:', local_path)\n",
+    "                print('Remote Path:', remote_path)\n",
+    "                \n",
+    "                # Download the file using your existing download_file function\n",
+    "                # Or you could directly insert the AWS S3 command here\n",
+    "                download_file(file_dict)\n",
+    "        \n",
+    "        # Update the progress bar\n",
+    "        pbar.update(1)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d0f38354-5cef-49ab-87d4-e6db5d913c65",
+   "metadata": {},
+   "source": [
+    "### Download individual files from WMB-10Xv2 [log2 file]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c27c7e77-a66f-4b40-a850-f600672feb98",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:   0%|          | 0/13 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "size: 8356210362\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-2-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-2-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-2-log2.h5ad 8356210362\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-2-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-2-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:   8%|▊         | 1/13 [01:29<17:59, 89.94s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.154994764\n",
+      "size: 4067049816\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-PAL-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-PAL-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-PAL-log2.h5ad 4067049816\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-PAL-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-PAL-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  15%|█▌        | 2/13 [02:27<12:59, 70.84s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.09150522900000002\n",
+      "size: 3277343842\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CTXsp-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CTXsp-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CTXsp-log2.h5ad 3277343842\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CTXsp-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CTXsp-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  23%|██▎       | 3/13 [03:13<09:57, 59.73s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.0702136659999999\n",
+      "size: 13726487690\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MB-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MB-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MB-log2.h5ad 13726487690\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MB-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MB-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  31%|███       | 4/13 [05:48<14:34, 97.21s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.29393174600000016\n",
+      "size: 5610691342\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CB-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CB-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CB-log2.h5ad 5610691342\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CB-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-CB-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  38%|███▊      | 5/13 [07:06<12:01, 90.21s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.10694514100000019\n",
+      "size: 11768194128\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-1-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-1-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-1-log2.h5ad 11768194128\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-1-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-Isocortex-1-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  46%|████▌     | 6/13 [09:23<12:22, 106.09s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.23650742900000044\n",
+      "size: 3114998442\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-OLF-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-OLF-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-OLF-log2.h5ad 3114998442\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-OLF-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-OLF-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  54%|█████▍    | 7/13 [10:06<08:33, 85.60s/it] "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.06603658600000006\n",
+      "size: 7206054638\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MY-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MY-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MY-log2.h5ad 7206054638\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MY-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-MY-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  62%|██████▏   | 8/13 [11:35<07:12, 86.57s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.2007744960000002\n",
+      "size: 5811140682\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-TH-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-TH-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-TH-log2.h5ad 5811140682\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-TH-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-TH-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  69%|██████▉   | 9/13 [13:06<05:51, 87.84s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.14923390299999983\n",
+      "size: 7248338584\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HY-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HY-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HY-log2.h5ad 7248338584\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HY-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HY-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  77%|███████▋  | 10/13 [14:51<04:39, 93.18s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.2323855539999995\n",
+      "size: 11915297204\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-STR-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-STR-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-STR-log2.h5ad 11915297204\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-STR-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-STR-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  85%|████████▍ | 11/13 [17:49<03:58, 119.23s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.4460739449999993\n",
+      "size: 5200570200\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-P-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-P-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-P-log2.h5ad 5200570200\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-P-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-P-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files:  92%|█████████▏| 12/13 [19:17<01:49, 109.76s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.21700768500000045\n",
+      "size: 7409633208\n",
+      "Local Path: /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HPF-log2.h5ad\n",
+      "Remote Path: s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HPF-log2.h5ad\n",
+      "expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HPF-log2.h5ad 7409633208\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HPF-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv3/20230630/WMB-10Xv3-HPF-log2.h5ad\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Downloading Files: 100%|██████████| 13/13 [21:16<00:00, 98.20s/it] "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "time taken:  0.28977505599999986\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialize the dictionary\n",
+    "expression_matrices = manifest['file_listing']['WMB-10Xv3']['expression_matrices']\n",
+    "\n",
+    "# Initialize the tqdm progress bar\n",
+    "categories = list(expression_matrices.keys())\n",
+    "with tqdm(total=len(categories), desc=\"Downloading Files\") as pbar:\n",
+    "\n",
+    "    # Iterate over the keys, which represent different categories\n",
+    "    for category in categories:\n",
+    "        \n",
+    "        # Look for 'log2' key in each category dictionary\n",
+    "        if 'log2' in expression_matrices[category]:\n",
+    "            \n",
+    "            # Get the 'files' dictionary under 'log2'\n",
+    "            files_dict = expression_matrices[category]['log2']['files']\n",
+    "            \n",
+    "            # Check if 'h5ad' format files are present\n",
+    "            if 'h5ad' in files_dict:\n",
+    "                file_dict = files_dict['h5ad']\n",
+    "                \n",
+    "                # Prepare the local and remote paths for downloading\n",
+    "                local_path = os.path.join(download_base, file_dict['relative_path'])\n",
+    "                local_path = pathlib.Path(local_path)\n",
+    "                remote_path = manifest['resource_uri'] + file_dict['relative_path']\n",
+    "                \n",
+    "                # Print size and paths before downloading\n",
+    "                print('size:', file_dict['size'])\n",
+    "                print('Local Path:', local_path)\n",
+    "                print('Remote Path:', remote_path)\n",
+    "                \n",
+    "                # Download the file using your existing download_file function\n",
+    "                # Or you could directly insert the AWS S3 command here\n",
+    "                download_file(file_dict)\n",
+    "        \n",
+    "        # Update the progress bar\n",
+    "        pbar.update(1)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "scverse",
+   "language": "python",
+   "name": "scverse"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/getting_started.ipynb b/notebooks/getting_started.ipynb
index ad3f9e3f..9bce3345 100644
--- a/notebooks/getting_started.ipynb
+++ b/notebooks/getting_started.ipynb
@@ -1,29 +1,12 @@
 {
  "cells": [
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "04304d1f-d7aa-4ba2-b181-14581bbd6217",
    "metadata": {
     "tags": []
    },
-   "source": [
-    "# Getting started\n",
-    "\n",
-    "Data associated with the Allen Brain Cell Atlas is hosted on Amazon Web Services (AWS) in an S3 bucket as a AWS Public Dataset. \n",
-    "No account or login is required. The S3 bucket is located here [arn:aws:s3:::allen-brain-cell-atlas](https://allen-brain-cell-atlas.s3.us-west-2.amazonaws.com/index.html). You will need to be connected to the internet to run this notebook.\n",
-    "\n",
-    "Each release has an associated **manifest.json** which list all the specific version of directories and files that are part of the release. We recommend using the manifest as the starting point of data download and usage.\n",
-    "\n",
-    "Expression matrices are stored in the [anndata h5ad format](https://anndata.readthedocs.io/en/latest/) and needs to be downloaded to a local file system for usage.\n",
-    "\n",
-    "The **AWS Command Line Interface ([AWS CLI](https://aws.amazon.com/cli/))** is a simple option to download specific directories and files from S3. Download and installation instructructions can be found here: https://aws.amazon.com/cli/. \n",
-    "\n",
-    "This notebook shows how to format AWS CLI commands to download the data required for the tutorials. You can copy those command onto a terminal shell or optionally you can run those command directly in this notebook by uncommenting the \"subprocess.run\" lines in the code.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
    "outputs": [],
    "source": [
     "import requests\n",
@@ -34,24 +17,13 @@
     "import time"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Using the file manifest"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's open the manifest.json file associated with the current release."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "id": "0a69f50b-1227-43f1-aaa5-ff614f56eb21",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -68,17 +40,13 @@
     "print(\"version: \", manifest['version'])"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "At the top level, the manifest consists of the release *version* tag, S3 *resource_uri*,  dictionaries *directory_listing* and *file_listing*. A simple option to download data is to use the AWS CLI to download specific directories or files. All the example notebooks in this repository assumes that data has been downloaded locally in the same file organization as specified by the \"relative_path\" field in the manifest."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {},
+   "id": "02f47998-4a18-4788-91c8-5fa1ae64d44d",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -95,17 +63,13 @@
     "print(\"resource_uri:\",manifest['resource_uri'])"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's look at the information associated with the spatial transcriptomics dataset **MERFISH-C57BL6J-638850**. This dataset has two related directories: *expression_matrices* containing a set of h5ad files and *metadata* containing a set of csv files. Use the *view_link* url to browse the directories on a web-browser."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {},
+   "id": "43f741ea-3039-47de-b2b5-c4ed5693f425",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -125,7 +89,10 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {},
+   "id": "2262220a-6737-4751-b2d6-49fbce2b002d",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -142,17 +109,13 @@
     "print(metadata['view_link'])"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Directory sizes are also reported as part to the manifest.json. WARNING: the expression matrices directories can get very large > 100 GB."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {},
+   "id": "463379c3-aeae-491a-a3dd-ce319d3d596d",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -165,12 +128,12 @@
       "expression_matrices/WMB-10Xv3/20230630 : 176.41 GB\n",
       "expression_matrices/WMB-10XMulti/20230830 : 0.21 GB\n",
       "metadata/WMB-10X/20230830 : 2.39 GB\n",
-      "metadata/WMB-taxonomy/20230830 : 0.00 GB\n",
+      "metadata/WMB-taxonomy/20230830 : 0.01 GB\n",
       "metadata/WMB-neighborhoods/20230830 : 3.00 GB\n",
       "image_volumes/Allen-CCF-2020/20230630 : 0.37 GB\n",
       "metadata/Allen-CCF-2020/20230630 : 0.00 GB\n",
       "image_volumes/MERFISH-C57BL6J-638850-CCF/20230630 : 0.11 GB\n",
-      "metadata/MERFISH-C57BL6J-638850-CCF/20230830 : 0.59 GB\n",
+      "metadata/MERFISH-C57BL6J-638850-CCF/20230830 : 2.01 GB\n",
       "expression_matrices/Zhuang-ABCA-1/20230830 : 3.09 GB\n",
       "metadata/Zhuang-ABCA-1/20230830 : 1.33 GB\n",
       "metadata/Zhuang-ABCA-1-CCF/20230830 : 0.21 GB\n",
@@ -197,61 +160,58 @@
     "        "
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Downloading files for the tutorial notebooks"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Suppose you would like to download data to your local path *../abc_download_root*."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {},
+   "id": "2ad6f441-acee-44b5-a68c-452add00689e",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "download_base = '../../abc_download_root'"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Downloading all metadata directories\n",
-    "\n",
-    "Since the metadata directories are relatively small we will download all the metadata directories. We loop through the manifest and download each metadata directory using  **[AWS CLI](https://aws.amazon.com/cli/)** sync command. This should take < 5 minutes."
+    "download_base = '/shared/Data/abc_download_root'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {},
+   "id": "86cb9c41-ac1f-4209-9759-7f489a2e0c6d",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/MERFISH-C57BL6J-638850/20230830 ../../abc_download_root/metadata/MERFISH-C57BL6J-638850/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/WMB-10X/20230830 ../../abc_download_root/metadata/WMB-10X/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/WMB-taxonomy/20230830 ../../abc_download_root/metadata/WMB-taxonomy/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/WMB-neighborhoods/20230830 ../../abc_download_root/metadata/WMB-neighborhoods/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Allen-CCF-2020/20230630 ../../abc_download_root/metadata/Allen-CCF-2020/20230630\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/MERFISH-C57BL6J-638850-CCF/20230830 ../../abc_download_root/metadata/MERFISH-C57BL6J-638850-CCF/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-1/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-1/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-1-CCF/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-1-CCF/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-2/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-2/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-2-CCF/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-2-CCF/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-3/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-3/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-3-CCF/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-3-CCF/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-4/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-4/20230830\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-4-CCF/20230830 ../../abc_download_root/metadata/Zhuang-ABCA-4-CCF/20230830\n"
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/MERFISH-C57BL6J-638850/20230830 /shared/Data/abc_download_root/metadata/MERFISH-C57BL6J-638850/20230830\n",
+      "time taken:  0.04437648999999988\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/WMB-10X/20230830 /shared/Data/abc_download_root/metadata/WMB-10X/20230830\n",
+      "time taken:  0.06514278899999981\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/WMB-taxonomy/20230830 /shared/Data/abc_download_root/metadata/WMB-taxonomy/20230830\n",
+      "time taken:  0.0016731450000000425\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/WMB-neighborhoods/20230830 /shared/Data/abc_download_root/metadata/WMB-neighborhoods/20230830\n",
+      "time taken:  0.0854246139999999\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Allen-CCF-2020/20230630 /shared/Data/abc_download_root/metadata/Allen-CCF-2020/20230630\n",
+      "time taken:  0.0018774339999998446\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/MERFISH-C57BL6J-638850-CCF/20230830 /shared/Data/abc_download_root/metadata/MERFISH-C57BL6J-638850-CCF/20230830\n",
+      "time taken:  0.057746414999999995\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-1/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-1/20230830\n",
+      "time taken:  0.03554774199999988\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-1-CCF/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-1-CCF/20230830\n",
+      "time taken:  0.005821159000000131\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-2/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-2/20230830\n",
+      "time taken:  0.013644605999999948\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-2-CCF/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-2-CCF/20230830\n",
+      "time taken:  0.003017780000000192\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-3/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-3/20230830\n",
+      "time taken:  0.017215441999999914\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-3-CCF/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-3-CCF/20230830\n",
+      "time taken:  0.004403759999999979\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-4/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-4/20230830\n",
+      "time taken:  0.0033300099999999944\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/metadata/Zhuang-ABCA-4-CCF/20230830 /shared/Data/abc_download_root/metadata/Zhuang-ABCA-4-CCF/20230830\n",
+      "time taken:  0.0018146720000000727\n"
      ]
     }
    ],
@@ -274,25 +234,17 @@
     "        \n",
     "        start = time.process_time()\n",
     "        # Uncomment to download directories\n",
-    "        #result = subprocess.run(command.split(),stdout=subprocess.PIPE)\n",
-    "        #print(\"time taken: \", time.process_time() - start)\n",
-    "  "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Downloading one 10x expression matrix\n",
-    "The prerequisite to run the 10x part 1 notebook is to have downloaded the log2 version of the \"'WMB-10Xv2-TH'\" matrix (4GB). Download takes ~ 1 min depending on your network speed. \n",
-    "\n",
-    "We define a simple helper function to create the require AWS command. You can copy the command into a terminal shell to run or optionally run it inside this notebook if you uncomment the \"subprocess.run\" line of code."
+    "        result = subprocess.run(command.split(),stdout=subprocess.PIPE)\n",
+    "        print(\"time taken: \", time.process_time() - start)\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {},
+   "id": "6e0ba5ce-d6f2-4667-9ac8-4736ae7006d4",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def download_file( file_dict ) :\n",
@@ -307,14 +259,17 @@
     "\n",
     "    start = time.process_time()\n",
     "    # Uncomment to download file\n",
-    "    #result = subprocess.run(command.split(' '),stdout=subprocess.PIPE)\n",
-    "    #print(\"time taken: \", time.process_time() - start)"
+    "    result = subprocess.run(command.split(' '),stdout=subprocess.PIPE)\n",
+    "    print(\"time taken: \", time.process_time() - start)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {},
+   "id": "6f9845f1-2801-46eb-b31d-c1a70d8c3464",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -322,7 +277,8 @@
      "text": [
       "size: 4038679930\n",
       "expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad 4038679930\n",
-      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad ../../abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n"
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad /shared/Data/abc_download_root/expression_matrices/WMB-10Xv2/20230630/WMB-10Xv2-TH-log2.h5ad\n",
+      "time taken:  0.11746830100000016\n"
      ]
     }
    ],
@@ -333,24 +289,13 @@
     "download_file( file_dict )"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Downloading the MERFISH expression matrix"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The prerequisite to run the MERFISH part 1 notebook is to have downloaded the log2 version of the \"C57BL6J-638850\" matrix (7GB). Download takes ~3 mins depending on tour network speed."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {},
+   "id": "4cdb7845-c5ba-4ab8-b4a1-8fad4f673cd5",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -358,7 +303,8 @@
      "text": [
       "size: 7627589574\n",
       "expression_matrices/MERFISH-C57BL6J-638850/20230830/C57BL6J-638850-log2.h5ad 7627589574\n",
-      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/MERFISH-C57BL6J-638850/20230830/C57BL6J-638850-log2.h5ad ../../abc_download_root/expression_matrices/MERFISH-C57BL6J-638850/20230830/C57BL6J-638850-log2.h5ad\n"
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/MERFISH-C57BL6J-638850/20230830/C57BL6J-638850-log2.h5ad /shared/Data/abc_download_root/expression_matrices/MERFISH-C57BL6J-638850/20230830/C57BL6J-638850-log2.h5ad\n",
+      "time taken:  0.20187397499999982\n"
      ]
     }
    ],
@@ -371,17 +317,13 @@
     "    download_file( file_dict )"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The prerequisite to run the Zhuang MERFISH notebook is to have downloaded the log2 version of the expression matrices of all 4 brain specimens"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {},
+   "id": "1e84f23f-70eb-4402-8f36-8770683f4277",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -389,16 +331,20 @@
      "text": [
       "size: 2128478610\n",
       "expression_matrices/Zhuang-ABCA-1/20230830/Zhuang-ABCA-1-log2.h5ad 2128478610\n",
-      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-1/20230830/Zhuang-ABCA-1-log2.h5ad ../../abc_download_root/expression_matrices/Zhuang-ABCA-1/20230830/Zhuang-ABCA-1-log2.h5ad\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-1/20230830/Zhuang-ABCA-1-log2.h5ad /shared/Data/abc_download_root/expression_matrices/Zhuang-ABCA-1/20230830/Zhuang-ABCA-1-log2.h5ad\n",
+      "time taken:  0.05316929699999973\n",
       "size: 871420938\n",
       "expression_matrices/Zhuang-ABCA-2/20230830/Zhuang-ABCA-2-log2.h5ad 871420938\n",
-      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-2/20230830/Zhuang-ABCA-2-log2.h5ad ../../abc_download_root/expression_matrices/Zhuang-ABCA-2/20230830/Zhuang-ABCA-2-log2.h5ad\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-2/20230830/Zhuang-ABCA-2-log2.h5ad /shared/Data/abc_download_root/expression_matrices/Zhuang-ABCA-2/20230830/Zhuang-ABCA-2-log2.h5ad\n",
+      "time taken:  0.029438904999999682\n",
       "size: 1160586154\n",
       "expression_matrices/Zhuang-ABCA-3/20230830/Zhuang-ABCA-3-log2.h5ad 1160586154\n",
-      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-3/20230830/Zhuang-ABCA-3-log2.h5ad ../../abc_download_root/expression_matrices/Zhuang-ABCA-3/20230830/Zhuang-ABCA-3-log2.h5ad\n",
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-3/20230830/Zhuang-ABCA-3-log2.h5ad /shared/Data/abc_download_root/expression_matrices/Zhuang-ABCA-3/20230830/Zhuang-ABCA-3-log2.h5ad\n",
+      "time taken:  0.03181599700000026\n",
       "size: 106739752\n",
       "expression_matrices/Zhuang-ABCA-4/20230830/Zhuang-ABCA-4-log2.h5ad 106739752\n",
-      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-4/20230830/Zhuang-ABCA-4-log2.h5ad ../../abc_download_root/expression_matrices/Zhuang-ABCA-4/20230830/Zhuang-ABCA-4-log2.h5ad\n"
+      "aws s3 cp --no-sign-request s3://allen-brain-cell-atlas/expression_matrices/Zhuang-ABCA-4/20230830/Zhuang-ABCA-4-log2.h5ad /shared/Data/abc_download_root/expression_matrices/Zhuang-ABCA-4/20230830/Zhuang-ABCA-4-log2.h5ad\n",
+      "time taken:  0.0043707689999998856\n"
      ]
     }
    ],
@@ -411,26 +357,22 @@
     "    download_file( file_dict )"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Downloading all image volumes\n",
-    "\n",
-    "The prerequisite to run the CCF and MERFISH to CCF registration notebooks is to have downloaded the two set of image volumes."
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
+   "execution_count": 14,
+   "id": "46d541e5-fdb3-4e88-8ee5-7a3327f35876",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/image_volumes/Allen-CCF-2020/20230630 ../../abc_download_root/image_volumes/Allen-CCF-2020/20230630\n",
-      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/image_volumes/MERFISH-C57BL6J-638850-CCF/20230630 ../../abc_download_root/image_volumes/MERFISH-C57BL6J-638850-CCF/20230630\n"
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/image_volumes/Allen-CCF-2020/20230630 /shared/Data/abc_download_root/image_volumes/Allen-CCF-2020/20230630\n",
+      "time taken:  0.011111058999999646\n",
+      "aws s3 sync --no-sign-request s3://allen-brain-cell-atlas/image_volumes/MERFISH-C57BL6J-638850-CCF/20230630 /shared/Data/abc_download_root/image_volumes/MERFISH-C57BL6J-638850-CCF/20230630\n",
+      "time taken:  0.0045148890000001884\n"
      ]
     }
    ],
@@ -453,24 +395,17 @@
     "        \n",
     "        start = time.process_time()\n",
     "        # Uncomment to download directories\n",
-    "        #result = subprocess.run(command.split(),stdout=subprocess.PIPE)\n",
-    "        #print(\"time taken: \", time.process_time() - start)\n",
+    "        result = subprocess.run(command.split(),stdout=subprocess.PIPE)\n",
+    "        print(\"time taken: \", time.process_time() - start)\n",
     "  "
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "scverse",
    "language": "python",
-   "name": "python3"
+   "name": "scverse"
   },
   "language_info": {
    "codemirror_mode": {
@@ -482,9 +417,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.10.9"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 5
 }