GO_heatmap

GO_heatmap.r

library(org.Mm.eg.db); library(gplots); library(bioDist)

# get gene in GO cat
gGOcat <- list()
for(i in 1:dim(mrnaGO)[1]){
  gGOcat[[mrnaGO$GOBPID[i]]] <- as.vector(unlist(mget(mrnaGO$GOBPID[i], org.Mm.egGO2ALLEGS)))
}

# filter each GO cat by the genes found to be DE
f <- function(vecGO, vecDE){
  return(vecGO[which(vecGO %in% vecDE)])
}
gGOcat <- lapply(gGOcat, FUN=function(x){f(x, glist)})

mat <- matrix(nrow=length(gGOcat), ncol=length(gGOcat))
for(i in 1:length(gGOcat)) {
 for(j in 1:length(gGOcat)) {
   # intersect / union
   mat[i,j] <- (length(intersect(gGOcat[[i]], gGOcat[[j]])) / length(union(gGOcat[[i]], gGOcat[[j]])))
 }
}
rownames(mat) <- names(gGOcat)
colnames(mat) <- names(gGOcat)

goNames <- as.vector(unlist(mget(names(gGOcat), GOTERM)))
goNames <- as.vector(unlist(lapply(goNames, FUN=function(x){x@Term})))

goNames <- paste(goNames, names(gGOcat), sep=" - ")
colnames(mat) <- goNames
rownames(mat) <- goNames

# color scale
c1 <- rainbow(32,v=seq(0.5,1,length=32),s=seq(1,0.3,length=32),start=4/6,end=4.0001/6);
pie(rep(1,32),col=c1);   # show off these colors
c2 <- rainbow(32,v=seq(0.5,1,length=32),s=seq(1,0.3,length=32),start=1/6,end=1.0001/6);
pie(rep(1,32),col=c2);   # show off these colors
c3 <- c(c1,rev(c2));  # rev reverses the list
rm(c1,c2)

pdf(file='GO_heatmap.pdf', height=13, width=13)
heatmap.2(mat, col=c3, margins = c(20, 20), dist=function(x){cor.dist(x)}, trace='none', density.info='none', cexRow=0.5, cexCol=0.5)
dev.off()
# keep it clean
rm(mat, goNames, gGOcat, f)