Differential Expression Analysis On Rpkms - Contrasts And Contrasts Of Contrasts
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12.7 years ago

Dear all,

I'm looking for a tool (better would be a Bioconductor package) able to perform differential expression analysis on a table of RPKMs. I've seen so far only solutions implementing raw read counts, like DEGSeq, edgeR and BaySeq. And yeah, in this particular case I cannot transform RPKMs back to read counts.

Do you have any idea? Furthermore, a great advantage would be the capability of calculating significance of "contrasts of contrasts" analysis, i.e. of tetrafactorial designs.

E.g. having 4 conditions: WT control, WT treated, mutant control, mutant treated.

DE1 = WT treated vs. WT control
DE2 = mutant treated vs. mutant control

DE1DE2 = (mutant trated vs. mutant control) vs. (WT treated vs. WT control)

Something like the great limma does for microarrays. But on RNASeq RPKMs.

Thanks a lot for any hint! :-)

r rna • 3.9k views
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if you are more familiar with LIMMA, it now can handle RNAseq data. Check out the user guide: http://bioconductor.org/packages/release/bioc/vignettes/limma/inst/doc/usersguide.pdf

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Thanks Dave! Unfortunately, limma explicitly requires read counts, not RPKMs. I cite page 3 of the user guide: "The approach is to convert a table of sequence read counts into an expression object which can then be analysed as for microarray data."

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Do you want to go ahead with cufflinks output (which compute FPKM) data by some bioconductor package? .I am not sure, but i think all R packages are based on read count data and are suitable for differential expressions for genes only not for differential isoforms expression.

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I do use cummeRbund, but it's a mere wrapper of cuffdiff output (although very nice-looking), and it has no function of conversion to original raw read counts per isoform. AFAIK.

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12.6 years ago

Some useful thoughts on my question:

http://seqanswers.com/forums/showthread.php?t=18622

Conclusion: use edgeR and raw read counts. No complex designs for RPKMs

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