[BioC] Remove batch effect in small RNASeq study (SVA or others?)

[Gordon K Smyth]

Dear Shirley,

I would probably do it like this:

   library(edgeR)
   logCPM <- cpm(y,log=TRUE,prior.count=5)
   logCPM <- removeBatchEffect(logCPM, batch=batch)

Best wishes
Gordon

> Date: Sat, 26 Apr 2014 10:51:23 -0400
> From: shirley zhang <shirley0818 at gmail.com>
> To: Bioconductor Mailing List <bioconductor at stat.math.ethz.ch>
> Subject: [BioC] Remove batch effect in small RNASeq study (SVA or
> 	others?)
>
> I have a RNASeq paired-end data from two batches (8 samples from batch1,
> and 7 samples from batch2). After alignment using TopHat2, then I got count
> using HTseq-count, and FPKM value via Cufflinks. A big batch effect can be
> viewed in PCA using both log10(raw count) and log10(FPKM) value.
>
> I can NOT use the block factor in edgeR to remove batch effect since I need
> to first obtain residuals after adjusting for batch effect, then test the
> residuals for hundreds of thousands of SNPs (eQTL analysis).
>
> My question is how to remove batch effect without using edgeR:
>
> 1. is SVA ok for such a small sample size (N=15)?
> 2. If SVA does not work, any other suggestions?
>
> Many thanks,
> Shirley

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