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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: anndata overhaul, diverse contributions ☀

  • Gökcen Eraslan: diverse contributions ☀

  • Sergei Rybakov: diverse contributions ☀

  • Fidel Ramirez: plotting ☀

  • Tom White: distributed computing

  • Philipp Angerer: initial anndata conception/development, software quality ☀

  • Alex Wolf: initial anndata & scanpy conception/development ☀

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

News

COVID-19 datasets distributed as h5ad 2020-04-01

In a joint initiative, the Wellcome Sanger Institute, the Human Cell Atlas, and the CZI distribute datasets related to COVID-19 via anndata’s h5ad files: covid19cellatlas.org. It wasn’t anticipated that the initial idea of sharing and backing an on-disk representation of AnnData would become so widely adopted. Curious? Read up more on the format.

CZI grant 2019-11-14

Scanpy has been selected an essential open source software for science by CZI among 32 projects, along with giants such as Scipy, Numpy, Pandas, Matplotlib, scikit-learn, scikit-image/plotly, pip, jupyterhub/binder, Bioconda, Seurat, Bioconductor, and others.

Latest additions

On master

Bugfixes

  • Fixed the width of the progress bar when downloading data PR 1507 M Klein

  • Fixed log1p inplace on integer dense arrays PR 1400 I Virshup

  • Fixed marker_gene_overlap default value for top_n_markers PR 1464 MD Luecken

  • Fixed download path of pbmc3k_processed PR 1472 D Strobl

  • Fixed anndata version requirement for sc.concat PR 1491 I Virshup

1.6.0 2020-08-15

This release includes an overhaul of dotplot(), matrixplot(), and stacked_violin() (PR 1210 F Ramirez), and of the internals of rank_genes_groups() (PR 1156 S Rybakov).

Overhaul of dotplot(), matrixplot(), and stacked_violin() PR 1210 F Ramirez

  • An overhauled tutorial → tutorial: plotting/core.

  • New plotting classes can be accessed directly (e.g., DotPlot) or using the return_fig param.

  • It is possible to plot log fold change and p-values in the rank_genes_groups_dotplot() family of functions.

  • Added ax parameter which allows embedding the plot in other images.

  • Added option to include a bar plot instead of the dendrogram containing the cell/observation totals per category.

  • Return a dictionary of axes for further manipulation. This includes the main plot, legend and dendrogram to totals

  • Legends can be removed.

  • The groupby param can take a list of categories, e.g., groupby=[‘tissue’, ‘cell type’].

  • Added padding parameter to dotplot and stacked_violin. PR 1270

  • Added title for colorbar and positioned as in dotplot for matrixplot().

  • dotplot() changes:

    • Improved the colorbar and size legend for dotplots. Now the colorbar and size have titles, which can be modified using the colorbar_title and size_title params. They also align at the bottom of the image and do not shrink if the dotplot image is smaller.

    • Allow plotting genes in rows and categories in columns (swap_axes).

    • Using DotPlot, the dot_edge_color and line width can be modified, a grid can be added, and other modifications are enabled.

    • A new style was added in which the dots are replaced by an empty circle and the square behind the circle is colored (like in matrixplots).

  • stacked_violin() changes:

    • Violin colors can be colored based on average gene expression as in dotplots.

    • The linewidth of the violin plots is thinner.

    • Removed the tics for the y-axis as they tend to overlap with each other. Using the style method they can be displayed if needed.

Additions

Bug fixes