decoupler.pl.filter_by_expr

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decoupler.pl.filter_by_expr#

decoupler.pl.filter_by_expr(adata, group=None, lib_size=None, min_count=10, min_total_count=15, large_n=10, min_prop=0.7, cmap='viridis', kw_histplot=None, **kwargs)#

Plot to help determining the thresholds of the decoupler.pp.filter_by_expr function.

Parameters:

  • adata (AnnData) – Annotated data matrix with observations (rows) and features (columns).

  • cmap (str (default: 'viridis')) – Colormap to use.

  • group (str | None (default: None)) – Name of the adata.obs column to group by. If None, it assumes that all samples belong to one group.

  • lib_size (float | None (default: None)) – Library size. If None, default to the sum of reads per sample.

  • min_count (int (default: 10)) – Minimum count requiered per gene for at least some samples.

  • min_total_count (int (default: 15)) – Minimum total count required per gene across all samples.

  • large_n (int (default: 10)) – Number of samples per group that is considered to be “large”.

  • min_prop (float (default: 0.7)) – Minimum proportion of samples in the smallest group that express the gene.

  • kw_histplot (dict | None (default: None)) – Keyword arguments passed to seaborn.histplot.

  • ax – An existing matplotlib.axes._axes.Axes instance to plot on. If None, a new figure and axes will be created.

  • figsize – Size of the figure in inches as (width, height).

  • dpi – Dots per inch for the figure resolution.

  • return_fig – If True, plotting methods should return the figure object instead of showing it.

  • save – If set, path to save the plot automatically to a file.

Return type:

None | Figure

Returns:

If return_fig=True, returns matplotlib.figure.Figure instance.

Example

import decoupler as dc

adata = dc.ds.hsctgfb()
dc.pl.filter_by_expr(adata)
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