Question: pcaMethods: What is best suited for analysing log2cpm data?
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Entering edit mode
6 months ago
augihol • 20

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.

ADD COMMENTlink 6 months ago augihol • 20 • updated 6 months ago Kevin Blighe 43k
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Entering edit mode
6 months ago
Kevin Blighe 43k
Republic of Ireland

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

ADD COMMENTlink 6 months ago Kevin Blighe 43k

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