Packages for GO and KEGG analysis on RNAseq data

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Dear all,

We are two biologists (so very new in bioinformatic field...) working with =
RNAseq data and having little "troubles" with pathways analysis. We perform=
ed mRNA sequencing on 4 distinct cell populations to compare their transcri=
ptional profile (platform Illumina HiSeq 2000). Row reads were mapped using=
 TopHat and differential analysis was performed with edgeR+voom+limma packa=
ges. Our final output is a table (.txt file) for each contrast containing o=
ur 16058 expressed genes with respective log fold change, expression values=
 (normalized) and adjusted p-values. We wish to perform pathway enrichment =
analysis (first GO for a global level and KEGG for a more precise analysis)=
 to determine which pathways are enriched/depleted in specific cell populat=
ion compared to the others in order to infer cell-type specific functional =
signatures. However, we have difficulties to find an optimal method to do t=
his. We tried several packages (e.g gage, goseq) and web-based softwares (e=
.g GeneGO, AmiGO) and found different outputs (sometimes opposite results).=
 What could be the more "validated" method/package for these analysis? In a=
ddition, we found differences considering the input data (raw reads, log FC=
, a list of differentially expressed genes=85) and finally we don't underst=
and what should be the input data for the analysis (we think that it is dep=
endent of the package/method used=85). So, does anyone of you experiences w=
ith GO/KEGG for RNAseq and maybe help us to use a good quantification metho=
d please?

Thank you very much for your help.

Best,

Nicolas

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