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‎README.md‎

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DO NOT EDIT DIRECTLY.
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| name | description | datatypes | suffixes | link to full data | maintained by |
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|:------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------|:-----------------------------|:--------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------|:---------------------------------------------|
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| [eeg_ds003645s_hed_demo](https://github.com/bids-standard/bids-examples/tree/master/eeg_ds003645s_hed_demo) | Shows usage of Hierarchical Event Descriptor (HED) in .tsv files | anat, beh, eeg, micr, motion | KSSSleep, SPIM, beh, channels, coordsystem, defacemask, eeg, electrodes, events, headshape, motion, photo, samples, scans | [link](https://openneuro.org/datasets/ds003645) | [@VisLab](https://github.com/VisLab) |
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| [micr_SEM](https://github.com/bids-standard/bids-examples/tree/master/micr_SEM) | Example SEM dataset in PNG format with 1 sample imaged over 2 sessions | micr | SEM, photo, samples, sessions | [link](https://doi.org/10.5281/zenodo.5498378) | [@jcohenadad](https://github.com/jcohenadad) |
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| [micr_SEMzarr](https://github.com/bids-standard/bids-examples/tree/master/micr_SEMzarr) | Example SEM dataset in PNG and OME-ZARR format with 1 sample imaged over 2 sessions | micr | SEM, SPIM, samples, sessions | n/a | [@TheChymera](https://github.com/TheChymera) |
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| [micr_SPIM](https://github.com/bids-standard/bids-examples/tree/master/micr_SPIM) | Example SPIM dataset in OME-TIFF format with 2 samples from the same subject with 4 chunks each | micr | SPIM, photo, samples | [link](https://doi.org/10.5281/zenodo.5517223) | [@jcohenadad](https://github.com/jcohenadad) |
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| name | description | datatypes | suffixes | link to full data | maintained by |
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|:------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------|:-----------------------------|:--------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------|:---------------------------------------------|
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| [eeg_ds003645s_hed_demo](https://github.com/bids-standard/bids-examples/tree/master/eeg_ds003645s_hed_demo) | Shows usage of Hierarchical Event Descriptor (HED) in .tsv files | anat, beh, eeg, micr, motion | KSSSleep, SPIM, beh, channels, coordsystem, defacemask, eeg, electrodes, events, headshape, motion, photo, samples, scans | [link](https://openneuro.org/datasets/ds003645) | [@VisLab](https://github.com/VisLab) |
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| [micr_SEM](https://github.com/bids-standard/bids-examples/tree/master/micr_SEM) | Example SEM dataset in PNG format with 1 sample imaged over 2 sessions | micr | SEM, photo, samples, sessions | [link](https://doi.org/10.5281/zenodo.5498378) | [@jcohenadad](https://github.com/jcohenadad) |
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| [micr_SEMzarr](https://github.com/bids-standard/bids-examples/tree/master/micr_SEMzarr) | Example SEM dataset in PNG and OME-ZARR format with 1 sample imaged over 2 sessions | micr | SEM, SPIM, samples, sessions | n/a | [@TheChymera](https://github.com/TheChymera) |
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| [micr_SPIM](https://github.com/bids-standard/bids-examples/tree/master/micr_SPIM) | Example SPIM dataset in OME-TIFF format with 2 samples from the same subject with 4 chunks each | micr | SPIM, photo, samples | [link](https://doi.org/10.5281/zenodo.5517223) | [@jcohenadad](https://github.com/jcohenadad) |
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| [micr_XPCTzarr](https://github.com/bids-standard/bids-examples/tree/master/micr_XPCTzarr) | Example XPCT dataset in OME-ZARR format with 1 sample imaged | micr | XPCT, photo, samples, sessions | [link](https://human-organ-atlas.esrf.eu/datasets/572252538) | [@chourroutm](https://github.com/chourroutm) |
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### Motion
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‎dataset_listing.tsv‎

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micr_SEM Example SEM dataset in PNG format with 1 sample imaged over 2 sessions [link](https://doi.org/10.5281/zenodo.5498378) [@jcohenadad](https://github.com/jcohenadad) micr SEM, photo, samples, sessions
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micr_SEMzarr Example SEM dataset in PNG and OME-ZARR format with 1 sample imaged over 2 sessions [@TheChymera](https://github.com/TheChymera) micr SEM, SPIM, samples, sessions
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micr_SPIM Example SPIM dataset in OME-TIFF format with 2 samples from the same subject with 4 chunks each [link](https://doi.org/10.5281/zenodo.5517223) [@jcohenadad](https://github.com/jcohenadad) micr SPIM, photo, samples
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micr_XPCTzarr Example XPCT dataset in OME-ZARR format with 1 sample imaged [link](https://human-organ-atlas.esrf.eu/datasets/572252538) [@chourroutm](https://github.com/chourroutm) micr XPCT, photo, samples, sessions
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fnirs_tapping Example fNIRS measurement with three conditions from five subjects [link](https://doi.org/10.5281/zenodo.5529797) [@rob-luke](https://github.com/rob-luke) nirs channels, coordsystem, events, nirs, optodes, scans
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fnirs_automaticity 24 subjects performing (non-)automatic finger tapping and foot stepping [link](https://doi.org/10.34973/vesb-mh30) [@robertoostenveld](https://github.com/robertoostenveld) nirs channels, coordsystem, events, nirs, optodes, practicelogbook, scans
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motion_systemvalidation Example dataset of two different motion captured system recorded almost simultaneously, but no brain data [link](https://doi.org/10.6084/m9.figshare.20238006.v2) [@JuliusWelzel](https://github.com/JuliusWelzel) motion channels, motion, scans

‎genetics_ukbb/.bids-validator-config.json‎

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‎micr_XPCTzarr/README.md‎

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1 human brain sample imaged over 1 session.
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Example dataset with empty images containing X-ray phase-contrast tomography (XPCT) data to illustrate BIDS convention.
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Using NGFF nested directory format example

‎micr_XPCTzarr/code/data_retrieval.py‎

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from pathlib import Path
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import zarr.convenience
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import dask.array
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import ome_zarr, ome_zarr.io, ome_zarr.writer
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from numcodecs import Blosc, Delta
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import time
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"""
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You may use the following command to prepare a Python 3.8+ environment for the download of the dataset: `pip install -r data_retrieval_reqs.txt`
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"""
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data_path = Path("../sub-LADAF-2020-31/ses-01/micr/") # path to session
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data_path.mkdir(exist_ok=True) # create directory
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# short utility function
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def zarr_array(url,selector):
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print('Retrieving data from', url)
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n5_store = zarr.N5FSStore(url)
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root = zarr.group(store=n5_store)
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return dask.array.from_zarr(root[selector])
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dataset_full = zarr_array("gs://ucl-hip-ct-35a68e99feaae8932b1d44da0358940b/LADAF-2020-31/brain/25.08um_complete-organ_bm05/","s0") # get a dask.array.Array that points to the whole N5 dataset
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# default filters and compressors made the script crash; the ones below work:
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filters = [Delta(dtype='i4')]
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compressor = Blosc(cname='zstd', clevel=1, shuffle=Blosc.SHUFFLE)
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path_roi = data_path / "sub-LADAF-2020-31_ses-01_sample-brain_XPCT.ome.zarr" # full name of the dataset following BIDS specification
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print('Writing in', str(path_roi))
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tic = time.time()
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store = ome_zarr.io.parse_url(path_roi,mode="a").store # NB: `mode="a"` should allow overwrite but it does not at the moment, see https://github.com/ome/ome-zarr-py/issues/376
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root = zarr.group(store=store)
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ome_zarr.writer.write_image(image=dataset_full,
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group=root,
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scaler=None,
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axes=[
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{
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"name": "z",
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"type": "space",
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"units": "micrometer" # voxel size is an isotropic 25.08 um
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},
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{
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"name": "y",
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"type": "space",
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"units": "micrometer" # voxel size is an isotropic 25.08 um
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},
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{
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"name": "x",
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"type": "space",
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"units": "micrometer" # voxel size is an isotropic 25.08 um
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}
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], # axis order of the dataset following BIDS specification
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coordinate_transformations=[
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[
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{
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"scale": [
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25.08,
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25.08,
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25.08
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], # voxel size is an isotropic 25.08 um
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"type": "scale"
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}
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]
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],
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storage_options=dict(
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chunks=(512,512,512), # this chunk size may be altered depending on someone's needs
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filters=filters, # default filters made the script crash
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compressor=compressor # default compressors made the script crash
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)
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)
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toc = time.time()
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print('Writing completed in', (toc - tic)/60, 'min!')

‎micr_XPCTzarr/code/data_retrieval_reqs.txt‎

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dask[complete]
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zarr
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ome-zarr
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numcodecs
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gcsfs

‎micr_XPCTzarr/code/metadata_formatter.py‎

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import urllib.request
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import json
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"""
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You may use the following command to prepare a Python 3.8+ environment for the download of the dataset: `pip install -r metadata_formatter_reqs.txt`
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"""
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# The following metadata file can be downloaded from https://human-organ-atlas.esrf.eu/datasets/572252538
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metadata_txt_file_uri = 'https://ids.esrf.fr/ids/getData?sessionId=182d0a3b-de3b-4602-8caf-9bd91dc5b0e5&datafileIds=572252539' # This URI expires quite often
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req = urllib.request.urlopen(metadata_txt_file_uri)
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json_dict = {}
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for line in urllib.request.urlopen(metadata_txt_file_uri):
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text = line.decode('utf-8')
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if text.startswith('#') or text == '\r\n':
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pass
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else:
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s = text.replace('\t','').replace('\r\n','').replace('"', '').replace('N.A.', 'n/a').split('=')
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try:
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s[1] = int(s[1])
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except:
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try:
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s[1] = float(s[1])
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except:
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pass
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json_dict[s[0]] = s[1]
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json_obj = json.dumps(json_dict)
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print(json_obj)
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"""
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The metadata has been split into several files:
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- micr_XPCTzarr/samples.json
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- micr_XPCTzarr/sub-LADAF-2020-31/sub-LADAF-2020-31_sessions.tsv
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- micr_XPCTzarr/sub-LADAF-2020-31/ses-01/micr/sub-LADAF-2020-31_ses-01_sample-brain_XPCT.json
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Note that some fields are redundant.
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"""

‎micr_XPCTzarr/code/metadata_formatter_reqs.txt‎

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urllib3

‎micr_XPCTzarr/code/truncate_data.sh‎

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#!/bin/bash
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# Bash script to truncate all the files containing the binary chunked data as per ../../CONTRIBUTING.md
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# Modified from ../../CONTRIBUTING.md
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find ../sub-LADAF-2020-31/ses-01/micr/sub-LADAF-2020-31_ses-01_sample-brain_XPCT.ome.zarr/ -type f -regex ".*/[0-9]*" -exec truncate -s 0 {} +

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