omicverse.pl.plot_pca_variance_ratio

omicverse.pl.plot_pca_variance_ratio(adata, use_rep='scaled|original|pca_var_ratios', n_pcs=30, log=False, show=None, save=None)[source]

Plot PCA variance ratio to determine optimal number of principal components.

Parameters:

  • adata (AnnData object containing PCA results.)

  • use_rep (Key in adata.uns for variance ratios. Default: 'scaled|original|pca_var_ratios'.)

  • n_pcs (Number of principal components to plot. Default: 30.)

  • log (Whether to use logarithmic scale. Default: False.)

  • show (Show the figure. Default: None.)

  • save (Save the figure to file. Default: None.)

Returns:

  • None: Displays or saves the PCA variance ratio plot.

  • Examples – >>> import omicverse as ov >>> # Basic PCA variance ratio plot >>> ov.pp.pca(adata, n_pcs=50) >>> ov.utils.plot_pca_variance_ratio(adata, n_pcs=30) >>> # Custom variance ratios with log scale >>> ov.utils.plot_pca_variance_ratio(adata, n_pcs=50, log=True)