scanpy.pl.rank_genes_groups_stacked_violin
- scanpy.pl.rank_genes_groups_stacked_violin(adata, groups=None, n_genes=None, groupby=None, gene_symbols=None, *, var_names=None, min_logfoldchange=None, key=None, show=None, save=None, return_fig=False, **kwds)
Plot ranking of genes using stacked_violin plot (see
stacked_violin()
)- Parameters
- adata :
AnnData
AnnData
Annotated data matrix.
- groups :
str
|Sequence
[str
] |None
Union
[str
,Sequence
[str
],None
] (default:None
) The groups for which to show the gene ranking.
- n_genes :
int
|None
Optional
[int
] (default:None
) Number of genes to show. This can be a negative number to show for example the down regulated genes. eg: num_genes=-10. Is ignored if
gene_names
is passed.- gene_symbols :
str
|None
Optional
[str
] (default:None
) Column name in
.var
DataFrame that stores gene symbols. By defaultvar_names
refer to the index column of the.var
DataFrame. Setting this option allows alternative names to be used.- groupby :
str
|None
Optional
[str
] (default:None
) The key of the observation grouping to consider. By default, the groupby is chosen from the rank genes groups parameter but other groupby options can be used. It is expected that groupby is a categorical. If groupby is not a categorical observation, it would be subdivided into
num_categories
(seedotplot()
).- min_logfoldchange :
float
|None
Optional
[float
] (default:None
) Value to filter genes in groups if their logfoldchange is less than the min_logfoldchange
- key :
str
|None
Optional
[str
] (default:None
) Key used to store the ranking results in
adata.uns
.- show :
bool
|None
Optional
[bool
] (default:None
) Show the plot, do not return axis.
- save :
bool
|None
Optional
[bool
] (default:None
) If
True
or astr
, save the figure. A string is appended to the default filename. Infer the filetype if ending on {'.pdf'
,'.png'
,'.svg'
}.- ax
A matplotlib axes object. Only works if plotting a single component.
- return_fig :
bool
|None
Optional
[bool
] (default:False
) Returns
StackedViolin
object. Useful for fine-tuning the plot. Takes precedence overshow=False
.- **kwds
Are passed to
stacked_violin()
.
- adata :
- Returns
If
return_fig
isTrue
, returns aStackedViolin
object, else ifshow
is false, return axes dict
Examples
>>> import scanpy as sc >>> adata = sc.datasets.pbmc68k_reduced() >>> sc.tl.rank_genes_groups(adata, 'bulk_labels')
>>> sc.pl.rank_genes_groups_stacked_violin(adata, n_genes=4, ... min_logfoldchange=4, figsize=(8,6))