I am analyzing a dataset (treatment vs. control) each with three replicates. In the PCA plot one of the replicate samples (control) is positioned away from the other two replicates but the treatment samples are nicely clustered. How do you deal this scenario? Is there any required modifications to DESEQ2?
the simplest thing to do is just to remove the third control sample and proceed with the analysis: an outlier sample might increase the variability for a couple of genes, potentially leading to a higher dispersion estimate and thus less power to call DE genes.
If you want to dig deeper, you can produce MA plots / scatterplots of the outlier sample versus all the other samples, to see where exactly the differences are.
After all, the PCA only tells you that there are differences, not where they are.
As a third suggestion: compute the PCA manually (you can use the code of the plotPCA function) and
inspect the loadings (they are called "rotation" in the prcomp output):