what is the difference between prerank and single sample

[AEDWIP]

I am newbie

I read https://www.gsea-msigdb.org/gsea/doc/GSEAUserGuideFrame.html. There is a discussion about prerank. I did not see anything about single sample?

I am working with a single bulk gene expression data set (mRNA). I plan to use prerank() and TPM values

thanks

Andy

p.s. Is there a better place to ask questions like this? Also you might consider adding a link to the FAQ to the documentation

[zqfang]

I don't know where the better place is. may be gitter?

In short,

• prerank is used for comparing two group of samples (e.g. control and treatment), where the gene ranking are defined by your custom rank method (like t-statistic, signal-to-noise, et.al).
• ssGSEA is used for comparing individual samples to the rest of all, trying to find the gene signatures which samples shared the same (use ssGSEA when you have a lot of samples).

The statistic between prerank (GSEA) and ssGSEA are different. Assume that we have calculated each running enrichment score of your ranked input genes, then

• es for GSEA: max(running enrichment scores) or min(running enrichment scores)
• es for ssGSEA: sum(running enrichment scores)

Yep, I'll improve that

[AEDWIP]

thanks Zqfang. I really appreciate the work you have done on GSEApy.

a few more minor questions.

I am using prerank() on Gene expression data. I am using the GO-biologic processes data set. prerank () generates about 39 png files. I looked through the code but could not figure out why out of all the possible pathways plots these 29 were generated? What makes them special?

I have been filtering the result based on 'fdr' and 'pvalue, the sorting by 'nes'. None of my top pathways get plotted automatically. It was not obvious how I could generate the enrichment plot my self.

Minor request for enhancement. the pathway names in the results csv file do not match the names of the plots that are automatically generated. This makes hard to programmatically cause them to be displayed in my juypter notebook

Kind regards

Andy

[zqfang]

prerank() just generate the top n figures for you (same behavior to GSEA). The program is slow when generate a lot of plots. If you have 40 gene_sets, you could set graph_num=40.

You could also do your own plots in jupyter notebook if your pathway is not plotted. see here: https://gseapy.readthedocs.io/en/latest/gseapy_example.html#3.2-How-to-generate-your-GSEA-plot-inside-python-console

For the names of the plots, I have to strip some unnecessary characters (causing problems) when saving files. Let me see what I can do