Hello, I am using dds object for my RNA-seq data and I am creating PCA with my gene expression data, I am not getting clear visualization of my treatment or control. There is any other exploratory analysis or way to visualize clear separation between control or treated groups. I am using these commands in R studio:

dds <- DESeqDataSetFromMatrix(countData = new_count, colData = sample.data, design = ~ outcome_txt)
vsddds <- vst(dds, blind = FALSE)
plotPCA(vsddds, "outcome_txt")

This is not quite a Bioconductor question and would be more suited for Biostars.

One does not require visual separation of groups via a PCA bi-plot in order for an effect / difference to exist between groups. Also, the plotPCA function will [by default] only plot PC1 versus PC2, whereas the differences between your groups may be reflected by PC6, PC8, or PC25.

It is important to first understand what is PCA, what it does to your data, and what it is measuring. See my post on Biostars in order to get a quick intro on this:

• https://www.biostars.org/p/280615/#280634

Also see our vignette for PCAtools, a Bioconductor package, which helps an individual to explore their data via PCA.

• PCAtools: everything Principal Component Analysis

Kevin