liana.multi.nmf

liana.multi.nmf(adata: AnnData | None = None, df: DataFrame | None = None, n_components: int | None = None, k_range: range = range(1, 11), use_raw: bool = False, layer: str | None = None, inplace: bool = True, verbose: bool = False, **kwargs)

Fits NMF to an AnnData object.

Parameters:

adata

Annotated data object.

n_componentsint, None

Number of components to use. If None, the number of components is estimated using the elbow method.

k_rangerange

Range of components to test. Default: range(1, 10).

use_raw

Use raw attribute of adata if present.

layer

Layer in anndata.AnnData.layers to use. If None, use anndata.AnnData.X.

inplace

Whether to store results in place, or else to return them.

**kwargsdict

Keyword arguments to pass to sklearn.decomposition.NMF.

Returns:

If inplace is True, it will add NMF_W and NMF_H to the adata.obsm and adata.varm.

If n_components is None, it will also add nfm_errors and nfm_rank to adata.uns.

If inplace is False, it will return W and H, and if n_components is None, it will also return errors and n_components.

If n_components is None and inplace, errors and n_components will be assigned to adata.uns.

If df is provided, inplace is always False.