Perform pairwise Wilcoxon test, classify groups by significance and plot results

pairwise.wilcox.test.R

# ref:https://fabiomarroni.wordpress.com/2017/03/25/perform-pairwise-wilcoxon-test-classify-groups-by-significance-and-plot-results/
library(multcompView)
 
first.set<-cbind(rnorm(100,mean=1.8),1)
second.set<-cbind(rnorm(100,mean=0.9),2)
third.set<-cbind(rnorm(100,mean=1),3)
 
full<-rbind(first.set,second.set,third.set)
 
pp<-pairwise.wilcox.test(full[,1], full[,2], p.adjust.method = "none", paired = FALSE)
mymat<-tri.to.squ(pp$p.value)
myletters<-multcompLetters(mymat,compare="<=",threshold=0.05,Letters=letters)
 
boxplot(full[,1] ~ full[,2],ylab="Something nice",names=c("Set 1","Set 2","Set 3"),ylim=c(min(full[,1]),0.2+max(full[,1])))
text(c(1,2,3),0.1+max(full[,1]),c(myletters$Letters[1],myletters$Letters[2],myletters$Letters[3]))
 
tri.to.squ<-function(x)
{
rn<-row.names(x)
cn<-colnames(x)
an<-unique(c(cn,rn))
myval<-x[!is.na(x)]
mymat<-matrix(1,nrow=length(an),ncol=length(an),dimnames=list(an,an))
for(ext in 1:length(cn))
{
    for(int in 1:length(rn))
    {
    if(is.na(x[row.names(x)==rn[int],colnames(x)==cn[ext]])) next
    mymat[row.names(mymat)==rn[int],colnames(mymat)==cn[ext]]<-x[row.names(x)==rn[int],colnames(x)==cn[ext]]
    mymat[row.names(mymat)==cn[ext],colnames(mymat)==rn[int]]<-x[row.names(x)==rn[int],colnames(x)==cn[ext]]
    }
 
}
return(mymat)
}