Normalizing RNAseq for PCA and CCA
I've given an answer about using how I normalise for PCA here. PCA works best if the data are normal-ish, but as models go it is fairly robust to fairly large deviations from normal. Transforming is not essential, but if data can be easily transformed into something that looks a bit more normal, then conclusions derived from looking at the PCA should be a bit more robust.

I'm not familiar with canonical-correlation analysis (CCA), but because I see sums and square roots in the formulas, I would assume it has similar data cleaning requirements to PCA. Unfortunately the R documentation for cancor doesn't have any information about any assumptions made on the data.