[BioC] Running DESeq with 1000 samples

[Gordon K Smyth]

Dear Maoqi Xu,

You could use limma-voom instead, which will handle 1000 samples in a few 
seconds without the need for extra memory.

See:

  http://genomebiology.com/2014/15/2/R29

If you particularly wanted to stick to an exact negative binomial 
analysis, then you could consider edgeR which uses considerably less 
memory than DESeq for large datasets, but for so many samples voom would 
seem the way to go.

Best wishes
Gordon



> Date: Wed,  9 Jul 2014 11:58:23 -0700 (PDT)
> From: "Maoqi Xu [guest]" <guest at bioconductor.org>
> To: bioconductor at r-project.org, maoqixu at usc.edu
> Cc: DESeq Maintainer <sanders at fs.tum.de>
> Subject: [BioC] Running DESeq with 1000 samples
>
> Hi,

> I'm using DESeq to find the differential expressed genes between 2 
> populations. The RNA-seq data set has a total sample size of around 
> 1000. However, even I set the memory limit of R to 6 Gb, it still 
> reports the error that it cannot allocate vector of certain size. I 
> wonder if it's possible to use DESeq on this huge data set and how much 
> memory should be enough.
>
> Thank you!
>
> -- output of sessionInfo():
>
> NA
>
> --
> Sent via the guest posting facility at bioconductor.org.

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