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.
Follow changes in the release notes.
COVID-19 datasets distributed as
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.
An overhauled tutorial → tutorial: plotting/core.
New plotting classes can be accessed directly (e.g.,
DotPlot) or using the
It is possible to plot log fold change and p-values in the
rank_genes_groups_dotplot()family of functions.
axparameter 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.
groupbyparam can take a list of categories, e.g.,
groupby=[‘tissue’, ‘cell type’].
Added padding parameter to
stacked_violin. PR 1270
Added title for colorbar and positioned as in dotplot for
Improved the colorbar and size legend for dotplots. Now the colorbar and size have titles, which can be modified using the
size_titleparams. 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 (
dot_edge_colorand 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).
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.
Added highly variable gene selection strategy from Seurat v3 PR 1204 A Gayoso
Restrict sphinx version to <3.1, >3.0 PR 1297 I Virshup
dendrogramfor scipy 1.5 PR 1290 S Rybakov
.rawto translate gene symbols if applicable PR 1278 E Rice
diffmap(issue 1262) G Eraslan
spring_projectissue 1260 S Rybakov
Bumped version requirement of
LinearOperatorissue 1246 I Virshup