I have been using the following tutorial by Stephen Turner and Will Bush to look at some RNA-seq data.
http://www.gettinggeneticsdone.com/2015/12/tutorial-rna-seq-differential.html
Looking into GAGE's documentation, it looks like this tutorial is using it in a somewhat non-standard way. Specifically, it looks like they are using it to conduct a GSEA-esque analysis, feeding it a vector of fold changes annotated by Entrez IDs and looking for enrichment within pathways contained in the `kegg.sets.hs` object.
Were this a standard GSEA analysis, I would order transcripts by log2 fold change prior to analysis. In this use case of GAGE, should transcripts also be rank ordered prior to analysis? Running it both ways appears to make a large difference, at least in the case of my data.
I see. Yes, I have multiple transcripts/splice variants of a single gene mapping to a single Entrez ID in my user data. If I am understanding correctly, this is the source of the issue. The algorithm is simply selecting the first fold change value associated with a given gene ID for use in further computations and disregarding other gene isoforms. Correct me if I am wrong and thank you for your response.