ssGSEA: Accept a Series with gene names as index and return a dataframe

[olgabot]

Hello,
I'm very excited about a Python implementation of ssGSEA! I'd like to convert my gene expression values to pathway expression values by using applyto perform ssGSEA on every row of a pandas.DataFrame expression matrix. Right now, this looks like this:

expression.head().apply(
    lambda x: gp.ssgsea(x.reset_index(), gene_sets=gmt), 
    axis=1)

1. The reset_index() seems unnecessary for every row
2. Each run of ssgsea returns None, rather than returning the converted pathway enrichment. I'd rather not have to read a file for every single sample I have (~6,000 of them), so can ssgsea return the Series instead?

Warmest,
Olga

[olgabot]

It also seems unnecessary to perform the gene set filtering every single time for every sample, but rather do it once for all samples.

[zqfang]

Hi, @olgabot ,

1. reset_index() is necessary only if your input is a pd.Series, I could fixed this to support pd.Series with gene_names as index(install the latest PR)
2. actually, ssgsea() return a ssGSEA object, which has many attributes. sorry for the unclear docs. Please try:

    #for example:
    ss = gp.ssgsea(x, gene_sets=gmt)
     #res2d attr is a dataframe contains all final enrichment results. see fig blow.
     ss.res2d
     #results attr is a ordeddict contains all internal statistical testing values     
     ss.results

3. You are right, the filtering part could be done once. Even so, the most time-consuming part is calculating the statistics on null distributions. ssGSEA module is just designed for single run now.
   I will try to add a patch to improve filter rules soon.

Thank you very much for your great advice.

[zqfang]

now, gseapy 0.8.4 supports gct formats, series, and dataframe with only 1 column(index as gene symbols):

gss =  gp.ssgsea(expression, gene_sets="KEGG_2016")
# to get all results from a dict
gss.resultsOnSamples