Hi everybody
I'm struggling a bit trying to do GSEA of RNA-Seq data. I've ended up settling with a package known as GAGE (Generally Applicable Gene-set Enrichment). The main reason is that this algorithm is the only one I've been able to find that does not require 10+ biological replicates.
I'm then asking GAGE to do a paired comparison between treatment and control and for each pair this will give me some enrichment score. What I'm struggling with is what sort of method I should ask GAGE to use for statistical testing, as I have only two replicates.
The options are:
I think the correct test to use is the rank-based two sample t-test, but it would be nice if someone with more statistical knowledge could comment on my workflow.
I'm struggling a bit trying to do GSEA of RNA-Seq data. I've ended up settling with a package known as GAGE (Generally Applicable Gene-set Enrichment). The main reason is that this algorithm is the only one I've been able to find that does not require 10+ biological replicates.
The algorithms employed by GAGE is targetted toward microarray data and as such there are some adjustments that are necessary prior to analysis. Basically, I need to do a transformation to make the data homoscedastic and I need to do length bias correction.
I'm then asking GAGE to do a paired comparison between treatment and control and for each pair this will give me some enrichment score. What I'm struggling with is what sort of method I should ask GAGE to use for statistical testing, as I have only two replicates.
The options are:
- Two-sample T-test (either parametric or rank-based)
- One-sample z-test
- K-S test
I think the correct test to use is the rank-based two sample t-test, but it would be nice if someone with more statistical knowledge could comment on my workflow.
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