[BioC] False positives due to GC content correction - DESeq2

Michael Love michaelisaiahlove at gmail.com
Fri Aug 8 20:11:04 CEST 2014

hi Aditi,

Please include all the code you used for EDAseq and DESeq2, and the

How do you know there are false positive? Are these genes which you
know are not differentially expressed?

Your dispersion plots didn't come through. You can email those
attachments to my email address, and we will continue discussion on
the Bioc list.


On Fri, Aug 8, 2014 at 1:54 PM, Aditi [guest] <guest at bioconductor.org> wrote:
> Hi Mike,
> I have been trying to use DESeq2 for a differential analysis of Chipseq data using 8 T/N pairs. There is a lot of heterogeneity in the samples due to clinical differences ( tumor stage etc), total mapped reads ( some samples are much better than the others), batch effects ( since they were processed at different times and not by the same person). I wanted to correct atleast some of the biases starting with GC content and what I did was to use offsets from EDAseq as an input to DESeq2 and introduced the batch variable in the model.
> What I dont understand is that when I corrected for GC bias in the samples, the final results tend to have a lot of false positives. I have attached the dispersion plots for both the runs. I cant seem to figure why
>  -- output of sessionInfo():
> -
> --
> Sent via the guest posting facility at bioconductor.org.

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