Scanpy – Single-Cell Analysis in Python

Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.

Key Contributors

anndata graph | scanpy graph | ☀ = maintainer

• Isaac Virshup: lead developer since 2019 ☀

• Gökcen Eraslan: developer, diverse contributions ☀

• Sergei Rybakov: developer, diverse contributions ☀

• Fidel Ramirez: developer, plotting ☀

• Giovanni Palla: developer, spatial data

• Malte Luecken: developer, community & forum

• Lukas Heumos: developer, diverse contributions

• Philipp Angerer: developer, software quality, initial anndata conception ☀

• Alex Wolf: lead developer 2016-2019, initial anndata & scanpy conception

• Fabian Theis & lab: enabling guidance, support and environment

• Discuss usage on Discourse and development on GitHub.

• Get started by browsing tutorials, usage principles or the main API.

• Follow changes in the release notes.

• Find tools that harmonize well with anndata & Scanpy via the external API and the ecosystem page.

• Check out our contributing guide for development practices.

• Consider citing Genome Biology (2018) along with original references.

News

Scanpy hits 100 contributors! 2022-03-31

100 people have contributed to Scanpy’s source code!

Of course, contributions to the project are not limited to direct modification of the source code. 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.

Thanks to all our contributors for making this project possible!

New community channels 2022-03-31

We’ve moved our forums and have a new publicly available chat!

• Our discourse forum has migrated to a joint scverse forum (discourse.scverse.org).

• Our private developer Slack has been replaced by a public Zulip chat (scverse.zulipchat.com).

Toolkit for spatial (squidpy) and multimodal (muon) published 2022-02-01

Two large toolkits extending our ecosystem to new modalities have had their manuscripts published!

• Muon, a framework for multimodal has been published in Genome Biology.

• Squidpy a toolkit for working with spatial single cell data has been published in Nature Methods.

(past news)

Latest additions

Version 1.9

1.9.1 2022-04-05

Bug fixes

• normalize_total() works when Dask is not installed PR 2209 R Cannoodt

• Fix embedding plots by bumping matplotlib dependency to version 3.4 PR 2212 I Virshup

1.9.0 2022-04-01

Tutorials

• New tutorial on the usage of Pearson Residuals: → tutorial: tutorial_pearson_residuals J Lause, G Palla

• Materials and recordings for Scanpy workshops by Maren Büttner

Experimental module

• Added scanpy.experimental module! Currently contains functionality related to pearson residuals in scanpy.experimental.pp PR 1715 J Lause, G Palla, I Virshup. This includes:

  • normalize_pearson_residuals() for Pearson Residuals normalization

  • highly_variable_genes() for HVG selection with Pearson Residuals

  • normalize_pearson_residuals_pca() for Pearson Residuals normalization and dimensionality reduction with PCA

  • recipe_pearson_residuals() for Pearson Residuals normalization, HVG selection and dimensionality reduction with PCA

Features

• filter_rank_genes_groups() now allows to filter with absolute values of log fold change PR 1649 S Rybakov

• _choose_representation now subsets the provided representation to n_pcs, regardless of the name of the provided representation (should affect mostly neighbors()) PR 2179 I Virshup PG Majev

• scanpy.external.pp.scrublet() (and related functions) can now be used on AnnData objects containing multiple batches PR 1965 J Manning

• Number of variables plotted with 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 Yves33

• Dask arrays now work with scanpy.pp.normalize_total() PR 1663 G Buckley, I Virshup

• embedding_density() now allows more than 10 groups PR 1936 A Wolf

• Embedding plots can now pass colorbar_loc to specify the location of colorbar legend, or pass None to not show a colorbar PR 1821 A Schaar I Virshup

• 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 I Virshup

• print_versions() now uses session_info PR 2089 P Angerer I Virshup

Ecosystem

Multiple packages have been added to our ecosystem page, including:

• decoupler a for footprint analysis and pathway enrichement PR 2186 PB Mompel

• dandelion for B-cell receptor analysis PR 1953 Z Tuong

• CIARA a feature selection tools for identifying rare cell types PR 2175 M Stock

Bug fixes

• Fixed finding variables with use_raw=True and basis=None in scanpy.pl.scatter() PR 2027 E Rice

• Fixed scanpy.external.pp.scrublet() to address issue 1957 FlMai and ensure raw counts are used for simulation

• Functions in scanpy.datasets no longer throw OldFormatWarnings when using anndata 0.8 PR 2096 I Virshup

• Fixed use of 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 M Zaslavsky

• Removed pytables dependency by implementing read_10x_h5 with h5py due to installation errors on Windows PR 2064

• Fixed bug in scanpy.external.pp.hashsolo() where default value was set improperly PR 2190 B Reiz

• Fixed bug in scanpy.pl.embedding() functions where an error could be raised when there were missing values and large numbers of categories PR 2187 I Virshup