# Molecular heterogeneity in major urinary proteins of Mus musculus subspecies: potential candidates involved in speciation
# Jane L Hurst, Robert J Beynon, Stuart D Armstrong, Amanda J Davidson, Sarah A Roberts, Guadalupe Gómez-Baena, Carole M Smadja, Guila Ganem
#
#METHOD : SCALE ON LOG DATA
#Copy data from clipboard in Mac OS X 
data <- read.delim(pipe("pbpaste"), header=TRUE) 

#If not already installed
#install.packages("gplots")
#install.packages("devtools")

#Load necessary packages
library("gplots")
library("devtools")
library("RColorBrewer")

#Load latest version of heatmap.3 function
source_url("https://raw.githubusercontent.com/obigriffith/biostar-tutorials/master/Heatmaps/heatmap.3.R")

#Load the data
data1<-data[,19:32]
rownames=data$Sample
matrix<-data.matrix(data1)

#Create color side bars
Species_colors=c("brown2","blue")
gcol1=Species_colors[data$subspecies+1]
Sex_colors=c("lightpink","lightskyblue")
gcol2=Sex_colors[data$sex+1]
Area_colors=c("springgreen4","yellow2")
gcol3=Area_colors[data$zone+1]
Population_colors=colorRampPalette(brewer.pal(n = 11, "Spectral"))(15)
gcol4=Population_colors[data$Pop]
rlab=t(cbind(gcol1,gcol2,gcol3))
rownames(rlab)=c("Subspecies","Sex","Zone")
pal <- colorRampPalette(c("black", "green"))

#Define custom dist and hclust functions for use with heatmaps
mydist=function(c) {dist(c,method="euclidian")}
myclust=function(c) {hclust(c,method="median")}

#Create heatmap using custom heatmap.3 source code loaded above
heatmap.3(matrix, hclustfun=myclust, distfun=mydist, na.rm = TRUE, scale="none", dendrogram="both",
          Rowv=TRUE, RowSideColors=rlab, symbreaks=FALSE, key=TRUE, symkey=FALSE,
          density.info="none", trace="none", labCol=NULL, labRow=data$Sample, cexRow=0.5, 
          col=colorRampPalette(brewer.pal(n = 9, "Oranges"))(100),
          RowSideColorsSize=4, KeyValueName= "Relative proportion")