liana.method.compute_global_specificity

liana.method.compute_global_specificity#

liana.method.compute_global_specificity(adata, groupby, lr_sep='^', n_perms=1000, seed=1337, n_jobs=-1, verbose=False, use_raw=True, layer=None, uns_key='global_interactions')#

Computes group-specific ligand-receptor means and permutation-based p-values.

This function performs a one-sided permutation test to assess whether the observed group-specific means are significantly higher than expected by chance. P-values are computed using the formula (k + 1) / (n_perms + 1), where k is the number of permutations with values greater than or equal to the observed statistic.

Parameters:

  • adata (AnnData) – Annotated data object.

  • groupby (str) – Key to be used for grouping.

  • lr_sep (str | None (default: '^')) – Separator to use when joining ligand and receptor names into interactions.

  • n_perms (int (default: 1000)) – Number of permutations for the permutation test. If None, no p-values are computed.

  • seed (int (default: 1337)) – Random seed for reproducibility.

  • n_jobs (int (default: -1)) – Number of parallel jobs. Defaults to -1 (all available cores).

  • verbose (bool (default: False)) – Verbosity flag.

  • use_raw (bool (default: True)) – Use raw attribute of adata if present.

  • layer (str (default: None)) – Layer in anndata.AnnData.layers to use. If None, use anndata.AnnData.X.

  • uns_key (str (default: 'global_interactions')) – Key in adata.uns that contains the LIANA results. Default is 'liana_res'.

Return type:

None

Returns:

None. The result with ‘lr_mean’ and ‘pval’ is stored in adata.uns["global_interactions"].