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Old 09-12-2014, 01:20 AM   #85
Location: Switzerland

Join Date: Sep 2014
Posts: 12
Default Gage analysis for RNAseq

Dear all,

We are two biologists (so not bioinformaticians...) working with RNAseq data and having little "troubles" with pathways analysis. We performed RNA sequencing on 4 distinct cell populations to compare their transcriptional profile (platform Illumina HiSeq 2000). Row reads were mapped using TopHat and differential analysis was performed with edgeR+voom+limma packages. Our final output is a table (.txt file) for each contrast containing our 16058 expressed genes with respective log fold change, expression values (normalized) and adjusted p-values. We wish to perform pathway enrichment analysis to determine which pathways are enriched/depleted in our respective cell populations to examine for distinct functions and the gage pathway seems to be very complete for both GO and KEGG. However, we are not sure to use the good data for the analysis. Do we have to make the analysis separately for all the cell populations (loading into R only the log fold changes for all the genes for the contrast cell population A vs all the other cell populations) or do we have to load a table containing 4 columns (our 4 cell populations) with normalized log2 transformed expression values? It is not very clear for us... In addition, as we don't have a treated group vs another non-treated, we don't have a "biological reference" for the analysis, does it make sense to perform all the analysis with ref = NULL and samp = NULL?
We apologize for the very naive question.

Thank you for your help.
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