decoupler.run_viper

decoupler.run_viper(mat, net, source='source', target='target', weight='weight', pleiotropy=True, reg_sign=0.05, n_targets=10, penalty=20, batch_size=10000, min_n=5, verbose=False, use_raw=True)

Virtual Inference of Protein-activity by Enriched Regulon (VIPER).

VIPER (Alvarez et al., 2016) estimates biological activities by performing a three-tailed enrichment score calculation. For further information check the supplementary information of the decoupler manuscript or the original publication.

Alvarez M.J.et al. (2016) Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nat. Genet., 48, 838–847.

Parameters:

matlist, DataFrame or AnnData

List of [features, matrix], dataframe (samples x features) or an AnnData instance.

netDataFrame

Network in long format.

sourcestr

Column name in net with source nodes.

targetstr

Column name in net with target nodes.

weightstr

Column name in net with weights.

pleiotropybool

Logical, whether correction for pleiotropic regulation should be performed.

reg_signfloat

Pleiotropy argument. p-value threshold for considering significant regulators.

n_targetsint

Pleiotropy argument. Integer indicating the minimal number of overlaping targets to consider for analysis.

penaltyint

Number higher than 1 indicating the penalty for the pleiotropic interactions. 1 = no penalty.

batch_sizeint

Size of the batches to use. Increasing this will consume more memmory but it will run faster.

min_nint

Minimum of targets per source. If less, sources are removed.

verbosebool

Whether to show progress.

use_rawbool

Use raw attribute of mat if present.

Returns:

estimateDataFrame

VIPER scores. Stored in .obsm[‘viper_estimate’] if mat is AnnData.

pvalsDataFrame

Obtained p-values. Stored in .obsm[‘viper_pvals’] if mat is AnnData.