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Principal Components Analysis. A statistical method used to reduce the dimensionality of a dataset while keeping as much variance in the first principal components as possible. It can be used to visualise samples with many variables in 2-D or 3-D, thus allowing for a visual non-supervised grouping of points.

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I want to apply a dimensionality reduction method, such as PCA or tSNE, in order to enter it to some working algorithm to find principle curve for pathway analysis. …
asked Aug 4 '19 by David