What are the differences between GSVA and GSEA?
I got some idea from a toward data science post (link):
"GSVA builds on top of GSEA where a set of genes is characterized between two condition groups defined in the sample. GSEA works on how genes are behaving differently between the two groups defined."
from my own understanding,
GSEA first analyze the differences between the tumor vs normal group for each gene; then rank them and calculate the enrichment scores.
GSVA instead, first analyze each gene among all groups (including both tumor and normal) to get a distribution for each genes, then rank them and calculate the GSVA scores.
But what is the goal or usage for each of these methods?