The purpose of principal component analysis is to derive a small number of independent ... accounting for about 84% of the total variance. Subsequent components each contribute 5% or less. Figure 13.6 ...

Principal component analysis (PCA) is a mathematical algorithm ... we begin by looking at the proportion of the variance present in all genes contained within each principal component (Fig.

A principal component analysis of a covariance matrix is equivalent to an analysis of a weighted correlation matrix, where the weight of each variable is equal to its variance. Variables with large ...