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#' Show Principal Components Breakdown
#'
#' Function to show Principal Components statistics based on the OrthoMCL presence absence groupings.
#' @param mcl_data output of FormatAfterOrtho --list of 2 things-- 1: binary matrix indicating the presence / absence of genes in each OG and 2: vector of names of OGs
#' @return returns a named list of principal components and accompanying proportion of variance for each
#' @examples
#' CalculatePrincipalCoordinates(after_ortho_format)
#' @export
CalculatePrincipalCoordinates <- function(mcl_data){
pa <- t(mcl_data$pa_matrix)
# turn to numeric
x <- mapply(pa, FUN=as.numeric)
rows <- dimnames(pa)[[1]]
cols <- dimnames(pa)[[2]]
m <- matrix(data=x, ncol=length(cols), nrow=length(rows))
rownames(m) <- rows
colnames(m) <- cols
nm <- m[ , apply(m, 2, var) != 0]
prm <- prcomp(nm, scale=T)
pr_coor_mtx = prm$x
return(summary(prm)$importance[2,])
}
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