decoupler.tl.rankby_group

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decoupler.tl.rankby_group#

decoupler.tl.rankby_group(adata, groupby, reference='rest', method='t-test_overestim_var')#

Rank features for characterizing groups.

Parameters:

  • adata (AnnData) – Annotated data matrix with observations (rows) and features (columns).

  • groupby (str) – The key of the observations grouping to consider.

  • reference (str | list (default: 'rest')) – Reference group or list of reference groups to use as reference.

  • method (str (default: 't-test_overestim_var')) – Statistical method to use for computing differences between groups. Avaliable methods include: {'wilcoxon', 't-test', 't-test_overestim_var'}.

Return type:

DataFrame

Returns:

DataFrame with different features between groups.

Example

import decoupler as dc

adata, net = dc.ds.toy()
dc.mt.ulm(adata, net, tmin=3)
scores = dc.pp.get_obsm(adata, "score_ulm")
dc.tl.rankby_group(adata, groupby="group")
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