scanpy.pl.highly_variable_genes

scanpy.pl.highly_variable_genes(adata_or_result, *, log=False, show=None, highly_variable_genes=True, save=None)

Plot dispersions or normalized variance versus means for genes.

Produces Supp. Fig. 5c of Zheng et al. (2017) and MeanVarPlot() and VariableFeaturePlot() of Seurat.

Parameters:

adata

Result of highly_variable_genes().

log bool (default: False)

Plot on logarithmic axes.

show bool | None (default: None)

Show the plot, do not return axis.

save bool | str | None (default: None)

If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {{'.pdf', '.png', '.svg'}}.

Return type:

None

Examples

Compute and plot highly variable genes from raw PBMC data.

import scanpy as sc
adata = sc.datasets.pbmc3k()
sc.pp.normalize_total(adata, target_sum=1e4)
sc.pp.log1p(adata)
sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)
sc.pl.highly_variable_genes(adata)

Plot on logarithmic axes.

sc.pl.highly_variable_genes(adata, log=True)