Nothing
plotSegmentation <- function(CNVdata, segmentation, chromosomes, opt=0){
# opt=0 plots the means
# opt=1 plots the CN
num_of_chroms <- length(chromosomes);
if(num_of_chroms<=6){
rows <- 1;
cols <- num_of_chroms;
}else{
cols <- 6;
tmp1 <- round(num_of_chroms/cols);
tmp2 <- num_of_chroms/cols;
diff_tmp <- tmp1-tmp2;
if(diff_tmp==0){
rows <- tmp1;
}else{
rows <- tmp1+1;
}
}
par(mfrow=c(rows,cols));
for(i in 1:num_of_chroms){
curr_chr <- chromosomes[i];
data_table <- CNVdata[which(CNVdata[,1]==curr_chr),];
if(class(data_table)!="matrix"){
data_table <- t(as.matrix(data_table));
}
curr_seg <- segmentation[which(segmentation[,1]==curr_chr),];
if(class(curr_seg)!="matrix"){
curr_seg <- t(as.matrix(curr_seg));
}
min_lrr <- min(as.numeric(data_table[,4]))-0.5;
max_lrr <- max(as.numeric(data_table[,4]))+0.5;
if(opt==1 && min_lrr > -1.5){
min_lrr <- -1.5;
}
if(opt==1 && max_lrr < 1.5){
max_lrr <- 1.5;
}
plot(as.numeric(data_table[,4]), col="blue", xaxt="n", xlab="", ylab="LRR", main=paste("chromosome", curr_chr), ylim=c(min_lrr, max_lrr));
chr_size <- sum(as.numeric(curr_seg[,4]));
tmp <- 0*c(1:chr_size);
curr = 1;
for(i in 1:nrow(curr_seg)){
if(opt==0){
label = as.numeric(curr_seg[i,5]);
}
if(opt==1){
label = as.numeric(curr_seg[i,6]);
}
tmp[curr:(curr+as.numeric(curr_seg[i,4]))] <- label;
curr = (curr+as.numeric(curr_seg[i,4]));
}
lines(c(1:length(tmp)), tmp, col="red", lwd=2);
}
}
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