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* Update release notes (including some old ones)
* More updates to release notes
* Tutorial links + zulip link
* Tutorial links + zulip link
* Fix up doc index page
* Group release notes
* Update news
* Update ecosystem (+ add release notes)
* Expand on 100 contributors
* More rewording of contributor milestone
* dammit
Copy file name to clipboardExpand all lines: docs/ecosystem.md
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-[cirrocumulus](https://cirrocumulus.readthedocs.io/) via direct reading of `.h5ad` {small}`Broad Inst.`
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-[cell browser](https://cells.ucsc.edu/) via exporing through {func}`~scanpy.external.exporting.cellbrowser` {small}`UCSC`
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-[SPRING](https://github.com/AllonKleinLab/SPRING) via exporting through {func}`~scanpy.external.exporting.spring_project` {small}`Harvard Med`
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-[vitessce](http://vitessce.io) for purely browser based viewing of zarr formatted AnnData files {smaller}`Harvard Med`
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## Portals
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- the [Gene Expression Analysis Resource](https://umgear.org/) {small}`U Maryland`
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- the [Galaxy Project](https://humancellatlas.usegalaxy.eu) for the Human Cell Atlas [\[tweet\]](https://twitter.com/ExpressionAtlas/status/1151797848469626881) {small}`U Freiburg`
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- the [Expression Atlas](https://www.ebi.ac.uk/gxa/sc/help.html) {small}`EMBL-EBI`
> PASTE is a computational method to align and integrate spatial transcriptomics data across adjacent tissue slices by leveraging both gene expression similarity and spatial distances between spots.
> CIARA is an algorithm for feature selection, that aims for the identification of rare cell types via scRNA-Seq data in scanpy.
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## Annotation/ Enrichment Analysis
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###Annotation/ Enrichment Analysis
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Analyses using curated prior knowledge
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-[decoupler](https://github.com/saezlab/decoupler-py) is a collection of footprint enrichment methods that allows to infer transcription factor or pathway activities. {small}`Institute for Computational Biomedicine, Heidelberg University`
> PASTE is a computational method to align and integrate spatial transcriptomics data across adjacent tissue slices by leveraging both gene expression similarity and spatial distances between spots.
[100 people have contributed to Scanpy's source code!](https://github.com/theislab/scanpy/graphs/contributors)
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Of course, contributions to the project are not limited to direct modification of the source code.
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Many others have improved the project by building on top of it, participating in development discussions, helping others with usage, or by showing off what it's helped them accomplish.
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Thanks to all our contributors for making this project possible!
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## New community channels {small}`2022-03-31`
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We've moved our forums and have a new publicly available chat!
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* Our discourse forum has migrated to a joint scverse forum ([discourse.scverse.org](https://discourse.scverse.org)).
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* Our private developer Slack has been replaced by a public Zulip chat ([scverse.zulipchat.com](https://scverse.zulipchat.com)).
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## Toolkit for spatial (squidpy) and multimodal (muon) published {small}`2022-02-01`
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Two large toolkits extending our ecosystem to new modalities have had their manuscripts published!
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*[Muon](https://muon.readthedocs.io/), a framework for multimodal has been published in [Genome Biology](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02577-8).
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*[Squidpy](https://squidpy.readthedocs.io/) a toolkit for working with spatial single cell data has been published in [Nature Methods](https://www.nature.com/articles/s41592-021-01358-2).
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## scVelo on the cover of Nature Biotechnology {small}`2020-12-01`
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Scanpy's counterpart for RNA velocity, [scVelo](http://scvelo.org/), made it on the cover of [Nature Biotechnology](https://www.nature.com/nbt/volumes/38/issues/12)\[[tweet](https://twitter.com/NatureBiotech/status/1334647540030070792)\].
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- Standardized and expanded available arguments to the `sc.pl.rank_genes_groups*` family of functions. {pr}`1529` {smaller}`F Ramirez` {smaller}`I Virshup`
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\- See examples sections of {func}`~scanpy.pl.rank_genes_groups_dotplot` and {func}`~scanpy.pl.rank_genes_groups_matrixplot` for demonstrations.
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- {func}`scanpy.tl.tsne` now supports the metric argument and records the passed parameters {pr}`1854` {smaller}`I Virshup`
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- {func}`scanpy.external.pl.scrublet_score_distribution` now uses same API as other scanpy functions for saving/ showing plots {pr}`1741` {smaller}`J Manning`
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```{rubric} Ecosystem
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```
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- Fixed handling of `gene_symbols` argument in a number of `sc.pl.rank_genes_groups*` functions {pr}`1529` {smaller}`F Ramirez` {smaller}`I Virshup`
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- Fixed handling of `use_raw` for `sc.tl.rank_genes_groups` when no `.raw` is present {pr}`1895` {smaller}`I Virshup`
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- {func}`scanpy.pl.rank_genes_groups_violin` now works for `raw=False` {pr}`1669` {smaller}`M van den Beek`
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- {func}`scanpy.pl.dotplot` now uses `smallest_dot` argument correctly {pr}`1771` {smaller}`S Flemming`
- New tutorial on the usage of Pearson Residuals: {tutorial}`tutorial_pearson_residuals` {smaller}`J Lause, G Palla`
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-[Materials](https://github.com/theislab/scanpy-tutorials/tree/master/scanpy_workshop) and [recordings](https://www.youtube.com/playlist?list=PL4rcQcNPLZxWQQH7LlRBMkAo5NWuHX1e3) for Scanpy workshops by Maren Büttner
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```{rubric} Experimental module
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```
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- Added {mod}`scanpy.experimental` module! Currently contains functionality related to pearson residuals in {mod}`scanpy.experimental.pp` {pr}`1715` {smaller}`J Lause, G Palla, I Virshup`. This includes:
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- {func}`~scanpy.experimental.pp.normalize_pearson_residuals` for Pearson Residuals normalization
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- {func}`~scanpy.experimental.pp.highly_variable_genes` for HVG selection with Pearson Residuals
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- {func}`~scanpy.experimental.pp.normalize_pearson_residuals_pca` for Pearson Residuals normalization and dimensionality reduction with PCA
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- {func}`~scanpy.experimental.pp.recipe_pearson_residuals` for Pearson Residuals normalization, HVG selection and dimensionality reduction with PCA
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```{rubric} Features
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```
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- {func}`~scanpy.tl.filter_rank_genes_groups` now allows to filter with absolute values of log fold change {pr}`1649` {smaller}`S Rybakov`
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- {func}`~scanpy.pl.embedding_density` now allows more than 10 groups {pr}`1936` {smaller}`A Wolf`
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- {func}`~scanpy.logging.print_versions` now uses `session_info` {pr}`2089` {smaller}`P Angerer` {smaller}`I Virshup`
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-`_choose_representation` now subsets the provided representation to n_pcs, regardless of the name of the provided representation (should affect mostly {func}`~scanpy.pp.neighbors`) {pr}`2179` {smaller}`I Virshup` {smaller}`PG Majev`
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-Embedding plots now have a `dimensions` argument, which lets users select which dimensions of their embedding to plot and uses the same broadcasting rules as other arguments {pr}`1538` {smaller}`I Virshup`
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-{func}`scanpy.external.pp.scrublet` (and related functions) can now be used on `AnnData` objects containing multiple batches {pr}`1965` {smaller}`J Manning`
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- Number of variables plotted with {func}`~scanpy.pl.pca_loadings` can now be controlled with `n_points` argument. Additionally, variables are no longer repeated if the anndata has less than 30 variables {pr}`2075` {smaller}`Yves33`
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- Dask arrays now work with {func}`scanpy.pp.normalize_total` {pr}`1663` {smaller}`G Buckley, I Virshup`
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- {func}`~scanpy.pl.embedding_density` now allows more than 10 groups {pr}`1936` {smaller}`A Wolf`
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- Embedding plots can now pass `colorbar_loc` to specify the location of colorbar legend, or pass `None` to not show a colorbar {pr}`1821` {smaller}`A Schaar` {smaller}`I Virshup`
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- Embedding plots now have a `dimensions` argument, which lets users select which dimensions of their embedding to plot and uses the same broadcasting rules as other arguments {pr}`1538` {smaller}`I Virshup`
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- {func}`~scanpy.logging.print_versions` now uses `session_info` {pr}`2089` {smaller}`P Angerer` {smaller}`I Virshup`
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```{rubric}Experimental module
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```{rubric}Ecosystem
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```
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- Added {mod}`scanpy.experimental` module!
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Multiple packages have been added to our ecosystem page, including:
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-[decoupler](https://github.com/saezlab/decoupler-py) a for footprint analysis and pathway enrichement {pr}`2186` {smaller}`PB Mompel`
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-[dandelion](https://github.com/zktuong/dandelion) for B-cell receptor analysis {pr}`1953` {smaller}`Z Tuong`
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-[CIARA](https://github.com/ScialdoneLab/CIARA_python) a feature selection tools for identifying rare cell types {pr}`2175` {smaller}`M Stock`
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```{rubric} Bug fixes
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```
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- Added {func}`scanpy.experimental.pp.normalize_pearson_residuals` for Pearson Residuals normalization {pr}`1715` {smaller}`J Lause, G Palla, I Virshup`
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- Added {func}`scanpy.experimental.pp.normalize_pearson_residuals_pca` for Pearson Residuals normalization and PCA {pr}`1715` {smaller}`J Lause, G Palla, I Virshup`
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- Added {func}`scanpy.experimental.pp.highly_variable_genes` for HVG selection with Pearson Residuals {pr}`1715` {smaller}`J Lause, G Palla, I Virshup`
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- Added {func}`scanpy.experimental.pp.normalize_pearson_residuals_pca` for Pearson Residuals normalization and dimensionality reduction with PCA {pr}`1715` {smaller}`J Lause, G Palla, I Virshup`
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- Added {func}`scanpy.experimental.pp.recipe_pearson_residuals` for Pearson Residuals normalization, HVG selection and dimensionality reduction with PCA {pr}`1715` {smaller}`J Lause, G Palla, I Virshup`
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- Fixed finding variables with `use_raw=True` and `basis=None` in {func}`scanpy.pl.scatter` {pr}`2027` {smaller}`E Rice`
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- Fixed {func}`scanpy.external.pp.scrublet` to address {issue}`1957` {smaller}`FlMai` and ensure raw counts are used for simulation
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- Functions in {mod}`scanpy.datasets` no longer throw `OldFormatWarnings` when using `anndata``0.8` {pr}`2096` {smaller}`I Virshup`
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- Fixed use of {func}`scanpy.pp.neighbors` with `method='rapids'`: RAPIDS cuML no longer returns a squared Euclidean distance matrix, so we should not square-root the kNN distance matrix. {pr}`1828` {smaller}`M Zaslavsky`
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- Removed `pytables` dependency by implementing `read_10x_h5` with `h5py` due to installation errors on Windows {pr}`2064`
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- Fixed bug in {func}`scanpy.external.pp.hashsolo` where default value was set improperly {pr}`2190` {smaller}`B Reiz`
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- Fixed bug in {func}`scanpy.pl.embedding` functions where an error could be raised when there were missing values and large numbers of categories {pr}`2187` {smaller}`I Virshup`
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