Batch effect and DE using TCGA and my data

Question

[thaisenayane]

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

[Ram]

Please use the formatting bar (especially the code option) to present your post better. You can use backticks for inline code (`text` becomes text), or select a chunk of text and use the highlighted button to format it as a code block. I've done it for you this time.

Answer 1

[swbarnes2]

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.