## The function is currently defined as
function (pcx, pcy, scaling)
{
loadi = paste(getwd(), "/PCA_Data_", scaling, "/PCA_LoadingsMatrix.csv",
sep = "")
Loading <- read.csv(loadi, sep = ",", header = TRUE)
Loading.x <- Loading[, 2:ncol(Loading)]
rownames(Loading.x) <- Loading[, 1]
load.xlab = paste("Loading PC", pcx)
load.ylab = paste("Loading PC", pcy)
lim.load = c()
Max.pc1 = 1.1 * (max(Loading.x[, pcx]))
Min.pc1 = 1.1 * (min(Loading.x[, pcy]))
Mpc1 = c(Min.pc1 * 2, Max.pc1 * 2)
Max.pc2 = 1.1 * (max(Loading.x[, pcx]))
Min.pc2 = 1.1 * (min(Loading.x[, pcy]))
Mpc2 = c(Min.pc2 * 2, Max.pc2 * 2)
colcool = "Colors_Pvalues"
pwdcol = paste(getwd(), "/Univariate/Pvalues/", colcool,
sep = "")
col.pv = read.csv(pwdcol, header = TRUE)
col.pv = matrix(col.pv[, -1], ncol = 1)
dev.new()
plot(Loading.x[, pcx], Loading.x[, pcy], col = col.pv, xlab = load.xlab,
ylab = load.ylab, xlim = c(Min.pc1, Max.pc1), ylim = c(Min.pc2,
Max.pc2), main = "PCA - Loading Plot (Significance-colored variables)",
sub = "Variables in red showed Pvalue < 0.05")
axis(1, at = Mpc1, pos = c(0, 0), labels = FALSE, col = "grey",
lwd = 0.7)
axis(2, at = Mpc2, pos = c(0, 0), labels = FALSE, col = "grey",
lwd = 0.7)
text(Loading.x[, pcx], Loading.x[, pcy], labels = rownames(Loading.x),
cex = 0.6, pos = 1)
E = paste(getwd(), "/PCA_Data_", scaling, "Loading_PC", pcx,
"vsPC", pcy, "_Pvalues-colored.pdf", sep = "")
dev.copy2pdf(file = E)
}
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