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Batch effect and DE using TCGA and my data

Hello,

I'm trying to perform a differential gene expression analysis using some TCGA data that I reprocessed and my data. However I'm worried about the batch effect.

Normally to perform deseq I use this:

dds <- DESeqDataSetFromHTSeqCount(sampleTable = d, directory = directory, design= ~ batch)
dds <- estimateSizeFactors(dds)
dds <- DESeq(dds)

and then to plot an remove the batch effect I use this:

vsd <- vst(dds)
plotPCA(vsd, "batch")
assay(vsd) <- limma::removeBatchEffect(assay(vsd), vsd$batch)
plotPCA(vsd, "batch")

my doubt is about to perform differential gene expression after removing this batch effect with limma, is there any way? or DeSeq itself do this when I put batch as design?

Thanks

Thaise

rna-seq r
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updated by swbarnes2 swbarnes2 • written by thaisenayane • thaisenayane

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written by Ram Ram

1 answer

or DeSeq itself do this when I put batch as design?

Yes. Don't try to correct for it, just let DESeq take it into account when making its models. You can also incorporate the design when calculating the PCA plot.

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written by swbarnes2 swbarnes2

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