Re: edgeR: mixing technical replicates from Illumina HiSeq and MiSeq
Nick N <[email protected]> Fri, 29 Aug 2014 10:29:15 +0100
| Newsgroups | gmane.science.biology.informatics.conductor |
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| Message-ID | <CAHyxFd=yp+ZVMmNj0jg7nm6XBMd6q_BHtyV1y8KwqGLDmtO0xw@mail.gmail.com> |
Thanks Ryan and Nicolas! I was wondering whether there is some sort of decision tree that can be formalised. Nicolas, you would consider 3 options - merging, ignoring or adding a factor. Could you recommend some sort of cut-offs for each choice or is it more of a qualitative decision by looking at plots and PCA? By the way, my data is RNA-Seq - I forgot to mention it. Ryan, I would basically ask you the same question. On Fri, Aug 29, 2014 at 9:42 AM, Ryan <[email protected]> wrote: > Hi Nick, > > Thanks to the underlying theory behind dispersion estimation, you can > easily test whether your "technical replicates" really do represent > technical replicates. Specifically, read counts in technical replicates > should follow a Poisson distribution, which is a special case of the > negative binomial with zero dispersion. So, simply fit a model using edgeR > or DESeq2 with a separate coefficient for each group of technical > replicates. Thus all the experimental variation will be absorbed into the > model coefficients and the only thing left will be the technical > variability of of the replicates. For true technical replicates, the > dispersion should be zero for all genes. So if you estimate dispersions > using this model, and plotBCV/plotDispEsts shows the dispersion very near > to zero, then you can be confident that you really have technical > replicates. If the dispersion is nonzero, then there is some additional > source of unaccounted-for variation. > > I have used this method on a pilot dataset with several technical > replicates for each condition. edgeR said the dispersion was something like > 10^-3 or less for all genes except for the very low-expressed genes. > > -Ryan > > > On 8/28/14, 9:23 AM, Nick N wrote: > >> Hi, >> >> I have a study where a fraction of the samples have been replicated on 2 >> Illumina platforms (HiSeq and Miseq). These are technical replicates - the >> library preparation is the same using the same biological replicates - >> it's >> only the sequencing which is different. >> >> My hunch was that I shall introduce the platform as as an additional >> (blocking) factor in the analysis. Than I stumbled upon this post: >> >> https://stat.ethz.ch/pipermail/bioconductor/2010-April/033099.html >> >> It recommends pooling the replicates. The post seems to apply to a >> different case ("pure" technical replicates, i.e. no differences in the >> sequencing platform used) so I probably shall ignore it. But I still feel >> a >> bit uncertain of the best way to treat the technical replicates. Can you, >> please, advise me on this? >> >> many thanks! >> Nick >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> [email protected] >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane. >> science.biology.informatics.conductor >> > > [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor