This function is implemented in the unique function for univariate statistical analysis 'univariate'. This function performs Wilcoxon-mann Whitney U test of each variable in the data set according to the class definition provided in the second column of the file.
Usage
wmw(file)
Arguments
file
a connection or a character string giving the name of the file containing the variables (matrix columns) to test.
Details
For details see ?univariate.
Author(s)
Edoardo Gaude, Dimitrios Spiliotopoulos, Francesca Chignola, Silvia Mari, Andrea Spitaleri and Michela Ghitti
Examples
## The function is currently defined as
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)
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/Mann-Whitney_Tests/",
sep = "")
dir.create(dirout.wm)
for (i in 1:NoF) {
for (j in 1:NoF) {
if (i < j) {
ni = paste("r.", i, ".csv", sep = "")
nj = paste("r.", j, ".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
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
}
wmw.ij.pv = paste("WMWTest_pvalues_", i, "vs",
j, ".csv", sep = "")
assign(wmw.ij.pv, wilx.pv)
write.csv(wilx.pv, paste(dirout.wm, wmw.ij.pv,
sep = ""))
}
}
}
}