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Question: what's special about smartpca vs regular pca
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I know people use smartpca to check outliers and also save eigenvectors for population structures, and it seems to be a standard. My question is that what's so smart about smartpca? Is the result or method significantly different from any PCA packages, for example, pccomp in R? or does smartpca use some specially modeling methods where we can not find in other packages?

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