pcaMethods: What is best suited for analysing log2cpm data?

Question

[augihol]

Hey, I recently learned about the pcaMethods package at bioconductor, which offers the following:

• svdPca
• svdImpute
• Probabilistic PCA (ppca)
• Bayesian PCA (bpca)
• Inverse non-linear PCA (NLPCA
• Nipals PCA

I was wondering if there is any of these algorithms you prefer and in what circumstances or analysis you prefer using them.

Answer 1

[Kevin Blighe]

svdPCA is used mostly (<- needs verifying) as a result of the fact that it is implemented in the common / popular prcomp() function, used in both my own Bioconductor package, PCAtools, and in DESeq2's plotPCA() function, and likely others. Unless you are absolutely bonkers about PCA, you would want to explore the other methods.

Kevin