Deseq: Difference in number of reads

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Rushiraj Manchiganti ▴ 20

@rushiraj-manchiganti-6191

Last seen 10.3 years ago

Hi, I have got a set of RNA-seq data with the control sample having around 8 million reads and the treated samples in the range of 13-17 million reads. I was wondering if DESeq can handle this kind of difference in number of reads between samples? Or a down sampling of reads is necessary before DESeq? Regards, Rushiraj [[alternative HTML version deleted]]

DESeq DESeq • 1.4k views

ADD COMMENT • link updated 11.2 years ago by Michael Love 43k • written 11.2 years ago by Rushiraj Manchiganti ▴ 20

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Michael Love 43k

@mikelove

Last seen 18 hours ago

United States

hi Rushiraj, The DESeq/DESeq2 model takes care of differences in library size through estimation of a size factor, s_j in Equation (2) in the paper here http://genomebiology.com/2010/11/10/r106 See the manual page ?estimateSizeFactors for DESeq/DESeq2. Mike On Thu, Oct 17, 2013 at 11:38 AM, Rushiraj Manchiganti <rushirajm@gmail.com>wrote: > Hi, > > I have got a set of RNA-seq data with the control sample having around 8 > million reads and the treated samples in the range of 13-17 million reads. > I was wondering if DESeq can handle this kind of difference in number of > reads between samples? Or a down sampling of reads is necessary before > DESeq? > > Regards, > > Rushiraj > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]

ADD COMMENT • link 11.2 years ago Michael Love 43k

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Simon Anders ★ 3.8k

@simon-anders-3855

Last seen 4.4 years ago

Zentrum für Molekularbiologie, Universi…

Hi > I have got a set of RNA-seq data with the control sample having around 8 > million reads and the treated samples in the range of 13-17 million reads. > I was wondering if DESeq can handle this kind of difference in number of > reads between samples? Or a down sampling of reads is necessary before > DESeq? No, there is no need to downsample. The statistical methods of DESeq and DESeq2 are designed to deal with this. Simon

ADD COMMENT • link 11.2 years ago Simon Anders ★ 3.8k

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Dear Sir, Thank you for your guidance. :) I will proceed with my analysis. Regards, Rushiraj On Thu, Oct 17, 2013 at 9:25 PM, Simon Anders <anders@embl.de> wrote: > Hi > > > I have got a set of RNA-seq data with the control sample having around 8 >> million reads and the treated samples in the range of 13-17 million reads. >> I was wondering if DESeq can handle this kind of difference in number of >> reads between samples? Or a down sampling of reads is necessary before >> DESeq? >> > > No, there is no need to downsample. The statistical methods of DESeq and > DESeq2 are designed to deal with this. > > Simon > > > ______________________________**_________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/**listinfo/bioconductor<https: stat.et="" hz.ch="" mailman="" listinfo="" bioconductor=""> > Search the archives: http://news.gmane.org/gmane.** > science.biology.informatics.**conductor<http: news.gmane.org="" gmane.="" science.biology.informatics.conductor=""> > [[alternative HTML version deleted]]

ADD REPLY • link 11.2 years ago Rushiraj Manchiganti ▴ 20

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