decoupler.decouple
- decoupler.decouple(mat, net, source='source', target='target', weight='weight', methods=None, args={}, consensus=True, cns_metds=None, min_n=5, verbose=True, use_raw=True)
Decouple function.
Runs simultaneously several methods of biological activity inference.
- Parameters:
- matlist, pd.DataFrame or AnnData
List of [features, matrix], dataframe (samples x features) or an AnnData instance.
- netpd.DataFrame
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.
- methodslist, str
List of methods to run. If none are provided use weighted top performers (mlm, ulm and wsum). To run all methods set to “all”.
- argsdict
A dict of argument-dicts.
- consensusbool
Boolean whether to run a consensus score between methods.
- cns_metdslist
List of estimate names to use for the calculation of the consensus score. If empty it will use all the estimates obtained after running the different methods.
- min_nint
Minimum of targets per source. If less, sources are removed.
- verbosebool
Whether to show progress.
- use_rawbool
If mat is AnnData, use its raw attribute.
- Returns:
- Returns dictionary of activity estimates and p-values or stores them in mat.obsm[‘method_estimate’] and
- mat.obsm[‘method_pvals’] for each method.