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.