decoupler.run_mlm

decoupler.run_mlm(mat, net, source='source', target='target', weight='weight', batch_size=10000, min_n=5, verbose=False, use_raw=True)

Multivariate Linear Model (MLM).

MLM fits a multivariate linear model for each sample, where the observed molecular readouts in mat are the response variable and the regulator weights in net are the covariates. Target features with no associated weight are set to zero. The obtained t-values from the fitted model are the activities (mlm_estimate) of the regulators in net.

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.

batch_sizeint

Size of the samples to use for each batch. 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

MLM scores. Stored in .obsm[‘mlm_estimate’] if mat is AnnData.

pvalsDataFrame

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