Principal component analysis (PCA) to obtain the principal components (PCs) that best fits the shape of the face in order to relate the SNP data with that PCs by using the partial least squares regression (PLSR) method as it is explained in Claes et al. 2014?
Don't understand very well the methodology there explained.
Thanks in advance.
PCA isn't method for regression but for data description. You can try PCA to find relation between SNP data and face shape data if you create one data matrix with both sets. Investigation loadings could tell something about relations.
Different approach to solve your task is to use some regression method for example PCR (principal component regression) or PLSR.
In my opinion there is no sense to calculate PLSR based on PCA data.
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