# Principal component analysis by several decomposition Classic List Threaded 1 message Reply | Threaded
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## Principal component analysis by several decomposition

 Hello,    I am coping with PCA obtained after several matrix decomposition of a data matrix containing biological information (for sake of completeness, matrix of metabolites and samples). I have a few of doubts about the procedure and results, then I will be greatfull to everyone who will address some (or all) of my issues. 1. Be X a m x n data matrix (n are variables/metabolites, m observables/samples), n is much greater than m; 2. I applied a scaling by Xm=zscore(X); 3. performed svd by [U S W]=svd(Xm); Assuming that W contains the principal components (PCs) of Xm (is it right, or I have to compute W'*Xm' to get them?), I can plot PCs one by one for each sample obtaining a biplot; now, how can I get the coefficients associated to each variables for each PCs? In addition, it seems that a more ready procedure is to compute pca by "princomp": [coeff,score,latent]=princomp(Xm) and in that case the coefficients are within the "coeff" matrix, but where are the PCs stored? Again, by computing PCs by eigenval decomposition: [V,D]=eig(cov(Xm)); I will get the V'*Xm' matrix which contains the PCs, but where are the coefficients? Thank you in advance -- Sent from: https://octave.1599824.n4.nabble.com/Octave-General-f1599825.html