vampire.anno.pl.motif_abundance_pca_variance

vampire.anno.pl.motif_abundance_pca_variance#

vampire.anno.pl.motif_abundance_pca_variance(adata, n_pcs=None, log=False, show_cumulative=True, figsize=(None, None), title=None, save=None, **kwargs)[source]#

Plot variance explained by each principal component.

Reads pre-computed results from vp.anno.tl.motif_abundance_pca() stored in uns['motif_abundance_pca']['variance_ratio'].

Parameters:

  • adata (AnnData) – Annotated data with PCA results.

  • n_pcs (int | None) – Number of PCs to display. If None, display all.

  • log (bool) – Use log scale for the variance-ratio axis.

  • show_cumulative (bool) – Overlay a cumulative-variance line on the same y-axis.

  • figsize (tuple[int | None, int | None]) – Figure size in pixels.

  • title (str | None) – Plot title.

  • **kwargs – Additional keyword arguments passed to fig.update_layout().

  • save (str | bool | 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'}.

Returns:

Bar + line plot of per-PC variance ratios.

Return type:

Figure

Examples

>>> import vampire as vp
>>> vp.anno.pl.set_default_plotstyle()
>>> adata = vp.datasets.wdr7_hprc()
>>> vp.anno.tl.motif_abundance_pca(adata)
>>> vp.anno.pl.motif_abundance_pca_variance(adata)
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