119 lines
2.5 KiB
R
119 lines
2.5 KiB
R
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plot_log2_fpkm_dist = function (fpkm_files) {
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num_files = length(fpkm_files);
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data_list = list();
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max_y = 0
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xlim = c(0,0)
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for (i in 1:num_files) {
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file = fpkm_files[i]
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data = read.table(file, header=F)
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data = data[,6];
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data = log2(data+1)
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den = density(data);
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data_list[[i]] = den
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y = max(den$y);
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if (y > max_y) {
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max_y = y;
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}
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x = min(den$x)
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if (x < xlim[1]) {
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xlim[2] = x
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}
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x = max(den$x);
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if (x > xlim[2]) {
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xlim[2] = x
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}
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}
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colors = rainbow(num_files);
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for (i in 1:num_files) {
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if (i == 1) {
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plot(data_list[[1]], col=colors[1], xlim=xlim, ylim=c(0,max_y), xlab="log2(fpkm+1)")
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}
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else {
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points(data_list[[i]], col=colors[i], type='l')
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}
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}
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return;
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}
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plot_expressed_gene_counts = function(fpkm_file,
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title="expressed transcript counts vs. min fpkm",
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fpkm_range=seq(0,10,0.2),
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total=0,
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outfile="count_summary.txt") {
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data = read.table(fpkm_file, header=T, row.names=1);
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data = data[,5]
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counts_expressed = c();
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counts_not_expressed = c();
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print_not_expressed_flag = 1;
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if (total == 0) {
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total = length(data);
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print_not_expressed_flag = 0;
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}
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count_expressed = total;
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for (i in fpkm_range) {
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if (i > 0) {
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count_expressed = sum(data>=i)
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}
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count_not_expressed = total - count_expressed;
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counts_expressed[length(counts_expressed)+1] = count_expressed;
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counts_not_expressed[length(counts_not_expressed)+1] = count_not_expressed;
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}
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orig_settings = par(mfrow=c(1,2))
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plot(fpkm_range, counts_expressed, type='o', col='black', xlab="min(fpkm)",
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main=title, ylab="count of transcripts", ylim=c(0,max(counts_expressed, counts_not_expressed)))
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if (print_not_expressed_flag) {
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points(fpkm_range, counts_not_expressed, type='o', col='blue')
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legend('topright', c('expressed', 'not expressed'), col=c('black', 'blue'), pch=15);
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}
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else {
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legend('bottomright', c('expressed transcripts'), col=c('black'), pch=15);
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}
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data_table = data.frame(fpkm_range=fpkm_range, expressed=counts_expressed, not_expressed=counts_not_expressed);
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write.table(data_table, file=outfile, quote=F, sep='\t', row.names=F);
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## make density plot for non-zero FPKM values
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data = data[data>0]
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plot(density(log2(data)), xlab="log2(fpkm)")
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par(orig_settings)
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}
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