Question: pcaMethods: What is best suited for analysing log2cpm data?
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gravatar for augihol
17 months ago by
augihol20
augihol20 wrote:

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.

rna-seq pca • 396 views
ADD COMMENTlink modified 17 months ago by Kevin Blighe63k • written 17 months ago by augihol20
0
gravatar for Kevin Blighe
17 months ago by
Kevin Blighe63k
Kevin Blighe63k wrote:

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 modified 17 months ago • written 17 months ago by Kevin Blighe63k
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