I am interested in using variance stabilized values of my data (that are the outputs of DESeq2's
varianceStabilizingTransformation function) for machine learning and other applications. I ran the following:
dds <- DESeqDataSetFromMatrix(countData = counts, colData = metadata, design = ~Institution + Condition) vsd <- varianceStabilizingTransformation(dds, blind = FALSE)
Although I tried to include the batch (Institution) in the design argument, I still see batches in my PCA plot. This section of the vignette described a solution for this that I have pasted below:
mat <- assay(vsd) mat <- limma::removeBatchEffect(mat, vsd$batch) assay(vsd) <- mat plotPCA(vsd)
Can the output of
removeBatchEffect in this code now be used for all other downstream applications, and not just for visualization?
Thanks very much.