
Compute the Euclidean distance among principal components.
pca2euclid(.pcaobj, .num.comps = 2)
An object returned by prcomp
.
On how many principal components compute the distance.
Matrix of distances.
# NOT RUN {
mat.ov <- repOverlap(AS_DATA, .norm = T)
mat.gen.pca <- pca.segments(AS_DATA, T, .genes = HUMAN_TRBV)
mat.ov.pca <- prcomp(mat.ov, scale. = T)
mat.gen.pca.dist <- pca2euclid(mat.gen.pca)
mat.ov.pca.dist <- pca2euclid(mat.ov.pca)
permutDistTest(mat.gen.pca.dist, list(<list of groups here>))
permutDistTest(mat.ov.pca.dist, list(<list of groups here>))
# }
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