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### Wilcoxon-Mann Whitney tests This function provide two.sided Wilcoxon Mann Whitney tests for each
### pairwise comparison of sample groups. file The connection to the data file. wmw(file) A matrix
### with p values
wmw <- function(file) {
pwdfile = paste(getwd(), "/Univariate/DataTable.csv", sep = "")
file = pwdfile
x <- read.csv(file, sep = ",", header = TRUE)
x.x = x[, 3:ncol(x)]
rownames(x.x) = x[, 2]
k = matrix(x[, 1], ncol = 1)
slink = paste(getwd(), "/DataPretreatment", "/slink.csv", sep = "")
slink = read.csv(slink, header = TRUE)
x.n = cbind(k, x.x)
sorted = x.n[order(x.n[, 1]), ]
g = c()
for (i in 1:nrow(sorted)) {
if (any(g == sorted[i, 1])) {
g = g
} else {
g = matrix(c(g, sorted[i, 1]), ncol = 1)
}
}
NoF = nrow(g)
dirout.wm = paste(getwd(), "/Univariate/MannWhitneyTests/", sep = "")
dir.create(dirout.wm)
for (i in 1:NoF) {
for (j in 1:NoF) {
if (i < j) {
ni = paste("r.", ExcName(i, slink), ".csv", sep = "")
nj = paste("r.", ExcName(j, slink), ".csv", sep = "")
pwdi = paste(getwd(), "/Univariate/Groups/", ni, sep = "")
pwdj = paste(getwd(), "/Univariate/Groups/", nj, sep = "")
I = read.csv(pwdi, header = TRUE)
J = read.csv(pwdj, header = TRUE)
I = I[, -1]
J = J[, -1]
fin = ncol(sorted) - 1
# perform WMW test for the effective combinations and extract p-values
wilx.pv <- matrix(rep(NA, fin))
for (q in 1:fin) {
wilx.pv[q, ] <- wilcox.test(I[, q], J[, q], paired = FALSE, exact = NULL, correct = FALSE,
conf.level = 0.95, alternative = "two.sided")$p.value
}
rownames(wilx.pv) <- colnames(x.x)
colnames(wilx.pv) <- c("pvalue")
wmw.ij.pv = paste("WMWTest_pvalues_", ExcName(i, slink), "vs", ExcName(j, slink),
".csv", sep = "")
assign(wmw.ij.pv, wilx.pv)
write.csv(wilx.pv, paste(dirout.wm, wmw.ij.pv, sep = ""))
}
}
}
}
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