score_mw

besca.tl.sig.score_mw(f: DataFrame, mymarkers: dict) → DataFrame[source]

Score Clusters based on a set of immune signatures to generate a df of pvals Takes as an input a dataframe with fractions per clusters and a dictionary of signatures Performs a Mann-Whitney test per each column and Signature, returns -10logpValues

Parameters:

  • f (panda.DataFrame) – a dataframe of -log10pvals per signature and cell cluster

  • mymarkers (Dictionary) – a dictionary of signatures

Returns:

a dataframe of -10logpValues per cluster and signature

Return type:

panda.DataFrame