386 lines
20 KiB
R
386 lines
20 KiB
R
plot.begin <- function(plotRoot, name, width=10, height=10) {
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if (!is.na(plotRoot)) {
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filename = paste(plotRoot, ".", name, ".pdf", sep="");
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print(sprintf("Plotting '%s' to '%s'", name, filename));
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pdf(filename, width=width, height=height);
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} else {
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print(sprintf("Plotting '%s' to X11", name));
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x11(width=width, height=height);
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}
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}
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plot.end <- function(plotRoot) {
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if (!is.na(plotRoot)) {
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dev.off();
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}
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}
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plot.venn <- function(a, b, c=0, a_and_b, a_and_c=0, b_and_c=0,
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col=c("#FF6342", "#63C6DE", "#ADDE63"),
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pos=c(0.20, 0.20, 0.80, 0.82),
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debug=0
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) {
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library(png);
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library(graphics);
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# Set up properties
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for (i in 1:length(col)) {
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rgbcol = col2rgb(col[i]);
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col[i] = sprintf("%02X%02X%02X", rgbcol[1], rgbcol[2], rgbcol[3]);
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}
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chco = paste(col[1], col[2], col[3], sep=",");
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chd = paste(a, b, c, a_and_b, a_and_c, b_and_c, sep=",");
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props = c(
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'cht=v',
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'chs=525x525',
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'chds=0,10000000000',
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paste('chco=', chco, sep=""),
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paste('chd=t:', chd, sep="")
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);
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proplist = paste(props[1], props[2], props[3], props[4], props[5], sep='&');
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# Get the venn diagram (as a temporary file)
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filename = tempfile("venn");
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cmd = paste("wget -O ", filename, " 'http://chart.apis.google.com/chart?", proplist, "' > /dev/null 2>&1", sep="");
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if (debug == 1) {
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print(cmd);
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}
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system(cmd);
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# Render the temp png file into a plotting frame
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a = readPNG(filename);
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plot(0, 0, type="n", xaxt="n", yaxt="n", bty="n", xlim=c(0, 1), ylim=c(0, 1), xlab="", ylab="");
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if (a >= b) {
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rasterImage(a, pos[1], pos[2], pos[3], pos[4]);
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} else {
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rasterImage(a, 0.37+pos[1], 0.37+pos[2], 0.37+pos[3], 0.37+pos[4], angle=180);
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}
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# Clean up!
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unlink(filename);
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}
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.attemptToLoadFile <- function(filename) {
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file = NA;
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if (file.exists(filename) & file.info(filename)$size > 500) {
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file = read.csv(filename, header=TRUE, comment.char="#");
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}
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file;
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}
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read.eval <- function(evalRoot) {
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fileAlleleCountStats = paste(evalRoot, ".AlleleCountStats.csv", sep="");
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fileCompOverlap = paste(evalRoot, ".Comp_Overlap.csv", sep="");
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fileCountVariants = paste(evalRoot, ".Count_Variants.csv", sep="");
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fileGenotypeConcordance = paste(evalRoot, ".Genotype_Concordance.csv", sep="");
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fileMetricsByAc = paste(evalRoot, ".MetricsByAc.csv", sep="");
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fileMetricsBySample = paste(evalRoot, ".MetricsBySample.csv", sep="");
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fileQuality_Metrics_by_allele_count = paste(evalRoot, ".Quality_Metrics_by_allele_count.csv", sep="");
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fileQualityScoreHistogram = paste(evalRoot, ".QualityScoreHistogram.csv", sep="");
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fileSampleStatistics = paste(evalRoot, ".Sample_Statistics.csv", sep="");
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fileSampleSummaryStatistics = paste(evalRoot, ".Sample_Summary_Statistics.csv", sep="");
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fileSimpleMetricsBySample = paste(evalRoot, ".SimpleMetricsBySample.csv", sep="");
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fileTi_slash_Tv_Variant_Evaluator = paste(evalRoot, ".Ti_slash_Tv_Variant_Evaluator.csv", sep="");
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fileTiTvStats = paste(evalRoot, ".TiTvStats.csv", sep="");
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fileVariant_Quality_Score = paste(evalRoot, ".Variant_Quality_Score.csv", sep="");
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eval = list(
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AlleleCountStats = NA,
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CompOverlap = NA,
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CountVariants = NA,
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GenotypeConcordance = NA,
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MetricsByAc = NA,
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MetricsBySample = NA,
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Quality_Metrics_by_allele_count = NA,
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QualityScoreHistogram = NA,
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SampleStatistics = NA,
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SampleSummaryStatistics = NA,
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SimpleMetricsBySample = NA,
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TiTv = NA,
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TiTvStats = NA,
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Variant_Quality_Score = NA,
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CallsetNames = c(),
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CallsetOnlyNames = c(),
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CallsetFilteredNames = c()
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);
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eval$AlleleCountStats = .attemptToLoadFile(fileAlleleCountStats);
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eval$CompOverlap = .attemptToLoadFile(fileCompOverlap);
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eval$CountVariants = .attemptToLoadFile(fileCountVariants);
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eval$GenotypeConcordance = .attemptToLoadFile(fileGenotypeConcordance);
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eval$MetricsByAc = .attemptToLoadFile(fileMetricsByAc);
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eval$MetricsBySample = .attemptToLoadFile(fileMetricsBySample);
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eval$Quality_Metrics_by_allele_count = .attemptToLoadFile(fileQuality_Metrics_by_allele_count);
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eval$QualityScoreHistogram = .attemptToLoadFile(fileQualityScoreHistogram);
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eval$SampleStatistics = .attemptToLoadFile(fileSampleStatistics);
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eval$SampleSummaryStatistics = .attemptToLoadFile(fileSampleSummaryStatistics);
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eval$SimpleMetricsBySample = .attemptToLoadFile(fileSimpleMetricsBySample);
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eval$TiTv = .attemptToLoadFile(fileTi_slash_Tv_Variant_Evaluator);
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eval$TiTvStats = .attemptToLoadFile(fileTiTvStats);
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eval$Variant_Quality_Score = .attemptToLoadFile(fileVariant_Quality_Score);
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uniqueJexlExpressions = unique(eval$TiTv$jexl_expression);
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eval$CallsetOnlyNames = as.vector(uniqueJexlExpressions[grep("FilteredIn|Intersection|none", uniqueJexlExpressions, invert=TRUE, ignore.case=TRUE)]);
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eval$CallsetNames = as.vector(gsub("-only", "", eval$CallsetOnlyNames));
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eval$CallsetFilteredNames = as.vector(c(
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paste(gsub("^(\\w)", "In\\U\\1", eval$CallsetNames[1], perl=TRUE), "-Filtered", gsub("^(\\w)", "In\\U\\1", eval$CallsetNames[2], perl=TRUE), sep=""),
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paste(gsub("^(\\w)", "In\\U\\1", eval$CallsetNames[2], perl=TRUE), "-Filtered", gsub("^(\\w)", "In\\U\\1", eval$CallsetNames[1], perl=TRUE), sep=""))
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);
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eval;
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}
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eval.getMetrics <- function(eval, jexl_expression) {
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callset.counts = eval$CountVariants[which(eval$CountVariants$evaluation_name == "eval" & eval$CountVariants$comparison_name == "dbsnp" & eval$CountVariants$jexl_expression == jexl_expression),];
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callset.counts.titv = eval$TiTv[which(eval$TiTv$evaluation_name == "eval" & eval$TiTv$comparison_name == "dbsnp" & eval$TiTv$jexl_expression == jexl_expression),];
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callset.calledCounts = callset.counts[which(callset.counts$filter_name == "called" & callset.counts$novelty_name == "all"),]$nVariantLoci;
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callset.calledCounts.titv = callset.counts.titv[which(callset.counts.titv$filter_name == "called" & callset.counts.titv$novelty_name == "all"),]$ti.tv_ratio;
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callset.knownCounts = callset.counts[which(callset.counts$filter_name == "called" & callset.counts$novelty_name == "known"),]$nVariantLoci;
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callset.knownCounts.titv = callset.counts.titv[which(callset.counts.titv$filter_name == "called" & callset.counts.titv$novelty_name == "known"),]$ti.tv_ratio;
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callset.novelCounts = callset.counts[which(callset.counts$filter_name == "called" & callset.counts$novelty_name == "novel"),]$nVariantLoci;
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callset.novelCounts.titv = callset.counts.titv[which(callset.counts.titv$filter_name == "called" & callset.counts.titv$novelty_name == "novel"),]$ti.tv_ratio;
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callset.allFilteredCounts = callset.counts[which(callset.counts$filter_name == "filtered" & callset.counts$novelty_name == "all"),]$nVariantLoci;
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callset.allFilteredCounts.titv = callset.counts.titv[which(callset.counts.titv$filter_name == "filtered" & callset.counts.titv$novelty_name == "all"),]$ti.tv_ratio;
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callset.knownFilteredCounts = callset.counts[which(callset.counts$filter_name == "filtered" & callset.counts$novelty_name == "known"),]$nVariantLoci;
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callset.knownFilteredCounts.titv = callset.counts.titv[which(callset.counts.titv$filter_name == "filtered" & callset.counts.titv$novelty_name == "known"),]$ti.tv_ratio;
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callset.novelFilteredCounts = callset.counts[which(callset.counts$filter_name == "filtered" & callset.counts$novelty_name == "novel"),]$nVariantLoci;
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callset.novelFilteredCounts.titv = callset.counts.titv[which(callset.counts.titv$filter_name == "filtered" & callset.counts.titv$novelty_name == "novel"),]$ti.tv_ratio;
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metrics = list(
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all = callset.calledCounts,
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all.titv = callset.calledCounts.titv,
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known = callset.knownCounts,
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known.titv = callset.knownCounts.titv,
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novel = callset.novelCounts,
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novel.titv = callset.novelCounts.titv,
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filtered.all = callset.allFilteredCounts,
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filtered.all.titv = callset.allFilteredCounts.titv,
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filtered.known = callset.knownFilteredCounts,
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filtered.known.titv = callset.knownFilteredCounts.titv,
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filtered.novel = callset.novelFilteredCounts,
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filtered.novel.titv = callset.novelFilteredCounts.titv
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);
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}
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.plot.callsetConcordance.getLabelText <- function(name, othername, metrics, filtered.metrics=NA, union) {
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if (is.na(filtered.metrics)) {
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text = sprintf("%s (%0.01f%% of union)\nCalled:\nAll: %d, Ti/Tv: %0.1f\nKnown: %d, Ti/Tv: %0.1f\nNovel: %d, Ti/Tv: %0.1f",
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name, 100*metrics$all/union$all.withfiltered,
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metrics$all, metrics$all.titv,
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metrics$known, metrics$known.titv,
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metrics$novel, metrics$novel.titv
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);
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} else {
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text = sprintf("%s (%0.01f%% of union)\nCalled in %s, absent in %s:\nAll: %d, Ti/Tv: %0.1f\nKnown: %d, Ti/Tv: %0.1f\nNovel: %d, Ti/Tv: %0.1f\n\nCalled in %s, filtered in %s:\nAll: %d, Ti/Tv: %0.1f\nKnown: %d, Ti/Tv: %0.1f\nNovel: %d, Ti/Tv: %0.1f",
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name, 100*(metrics$all + filtered.metrics$all)/union$all.withfiltered,
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name, othername,
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metrics$all, metrics$all.titv,
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metrics$known, metrics$known.titv,
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metrics$novel, metrics$novel.titv,
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name, othername,
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filtered.metrics$all, filtered.metrics$all.titv,
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filtered.metrics$known, filtered.metrics$known.titv,
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filtered.metrics$novel, filtered.metrics$novel.titv
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);
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}
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}
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plot.callsetConcordance <- function(eval, col=c("#FF6342", "#63C6DE", "#ADDE63")) {
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aonly = eval.getMetrics(eval, eval$CallsetOnlyNames[1]);
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aonly.filtered = eval.getMetrics(eval, eval$CallsetFilteredNames[1]);
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intersection = eval.getMetrics(eval, "Intersection");
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bonly = eval.getMetrics(eval, eval$CallsetOnlyNames[2]);
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bonly.filtered = eval.getMetrics(eval, eval$CallsetFilteredNames[2]);
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union = list(
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all = intersection$all + aonly$all + bonly$all,
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all.withfiltered = intersection$all + aonly$all + bonly$all + aonly.filtered$all + bonly.filtered$all
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);
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plot.venn(aonly$all + intersection$all + aonly.filtered$all, bonly$all + intersection$all + bonly.filtered$all, 0, intersection$all, 0, 0, pos=c(0.32, 0.32, 0.68, 0.70), col=col);
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text(0, 0.45, cex=1.2, pos=4, .plot.callsetConcordance.getLabelText(eval$CallsetNames[1], eval$CallsetNames[2], aonly, aonly.filtered, union));
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text(0.5, 0.75, cex=1.2, adj=c(0.5, 0.33), .plot.callsetConcordance.getLabelText("Intersection", NA, intersection, NA, union));
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text(1, 0.45, cex=1.2, pos=2, .plot.callsetConcordance.getLabelText(eval$CallsetNames[2], eval$CallsetNames[1], bonly, bonly.filtered, union));
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}
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plot.callsetConcordanceByAC <- function(eval, normalize=TRUE, novelty_name="all", col=c("#FF6342", "#5C92A4", "#55BBFF")) {
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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aonly.filtered = eval.getMetrics(eval, eval$CallsetFilteredNames[1]);
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intersection = eval.getMetricsByAc(eval, "Intersection", novelty_name);
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bonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[2], novelty_name);
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bonly.filtered = eval.getMetrics(eval, eval$CallsetFilteredNames[2]);
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title = paste("Callset concordance per allele count (", novelty_name, " variants)", sep="");
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if (length(intersection$AC) > 0 && length(aonly$AC) == 0) {
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aonly = intersection;
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aonly$n = 0;
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}
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if (length(intersection$AC) > 0 && length(bonly$AC) == 0) {
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bonly = intersection;
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bonly$n = 0;
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}
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#par.def = par(no.readonly = TRUE);
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#par(mar=c(5, 5, 3, 5));
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if (normalize == TRUE) {
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norm = aonly$n + intersection$n + bonly$n;
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matnorm = rbind(aonly$n/norm, intersection$n/norm, bonly$n/norm);
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barplot(matnorm, col=col, xlab="Allele count", ylab="Fraction", main=title, names.arg=intersection$AC, xlim=c(0, max(intersection$AC)), ylim=c(0, 1.3), border=NA);
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} else {
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mat = rbind(aonly$n, intersection$n, bonly$n);
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barplot(mat, col=col, xlab="Allele count", ylab="counts", main=title, names.arg=intersection$AC, xlim=c(0, max(intersection$AC)), ylim=c(0, 1), border=NA);
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}
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legend("topright", c(eval$CallsetOnlyNames[1], "Intersection", eval$CallsetOnlyNames[2]), fill=col);
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#par(par.def);
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}
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plot.alleleCountSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#5C92A4", "#55BBFF")) {
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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intersection = eval.getMetricsByAc(eval, "Intersection", novelty_name);
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bonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[2], novelty_name);
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title = paste("Allele count spectrum (", novelty_name, " variants)", sep="");
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if (length(intersection$AC) > 0 && length(aonly$AC) == 0) {
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aonly = intersection;
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aonly$n = 0;
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}
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if (length(intersection$AC) > 0 && length(bonly$AC) == 0) {
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bonly = intersection;
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bonly$n = 0;
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}
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suppressWarnings(plot(0, 0, type="n", xlim=c(1, length(intersection$AC)), ylim=c(1, max(aonly$n + intersection$n, bonly$n + intersection$n)), xlab="Allele count", ylab="Number of variants", main=title, log="xy", bty="n"));
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suppressWarnings(points(intersection$AC, aonly$n + intersection$n, type="l", lwd=2, col=col[1]));
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suppressWarnings(points(intersection$AC, intersection$n, type="l", lwd=2, col=col[2]));
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suppressWarnings(points(intersection$AC, bonly$n + intersection$n, type="l", lwd=2, col=col[3]));
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legend("topright", c(eval$CallsetOnlyNames[1], "Intersection", eval$CallsetOnlyNames[2]), fill=col);
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}
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eval.getMetricsByAc <- function(eval, jexl_expression, novelty_name="all") {
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piece = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(jexl_expression) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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}
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plot.titvSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#5C92A4", "#55BBFF")) {
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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intersection = eval.getMetricsByAc(eval, "Intersection", novelty_name);
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bonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[2], novelty_name);
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title = paste("Ti/Tv spectrum (", novelty_name, " variants)", sep="");
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if (length(intersection$AC) > 0 && length(aonly$AC) == 0) {
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aonly = intersection;
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aonly$n = 0;
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aonly$nTi = 0;
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aonly$nTv = 0;
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}
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if (length(intersection$AC) > 0 && length(bonly$AC) == 0) {
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bonly = intersection;
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bonly$n = 0;
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bonly$nTi = 0;
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bonly$nTv = 0;
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}
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titv.aonly = (aonly$nTi + intersection$nTi)/(aonly$nTv + intersection$nTv);
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titv.aonly.finite = titv.aonly[which(is.finite(titv.aonly))];
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titv.intersection.finite = intersection$Ti.Tv[which(is.finite(intersection$Ti.Tv))];
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titv.bonly = (bonly$nTi + intersection$nTi)/(bonly$nTv + intersection$nTv);
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titv.bonly.finite = titv.bonly[which(is.finite(titv.bonly))];
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titv.min = min(titv.aonly.finite, titv.intersection.finite, titv.bonly.finite);
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titv.max = max(titv.aonly.finite, titv.intersection.finite, titv.bonly.finite);
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plot(0, 0, type="n", xlim=c(1, length(intersection$AC)), ylim=c(titv.min, titv.max), xlab="Allele count", ylab="Transition/transversion (Ti/Tv) ratio", main=title, bty="n");
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points(intersection$AC, (aonly$nTi + intersection$nTi)/(aonly$nTv + intersection$nTv), type="l", lwd=2, col=col[1]);
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points(intersection$AC, intersection$Ti.Tv, type="l", lwd=2, col=col[2]);
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points(intersection$AC, (bonly$nTi + intersection$nTi)/(bonly$nTv + intersection$nTv), type="l", lwd=2, col=col[3]);
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abline(h=2.3, lty=2);
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mtext("2.3", side=4, at=2.3, cex=0.9);
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abline(h=3.3, lty=2);
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mtext("3.3", side=4, at=3.3, cex=0.9);
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legend("topleft", c(eval$CallsetOnlyNames[1], "Intersection", eval$CallsetOnlyNames[2]), fill=col);
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}
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plot.variantsPerSample2 <- function(eval) {
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if (!is.na(eval$MetricsBySample)) {
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metrics.all = eval$MetricsBySample[which(eval$MetricsBySample$evaluation_name == "eval" & eval$MetricsBySample$comparison_name == "dbsnp" & as.character(eval$MetricsBySample$jexl_expression) == "none" & eval$MetricsBySample$filter_name == "called" & eval$MetricsBySample$novelty_name == "all"),];
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metrics.known = eval$MetricsBySample[which(eval$MetricsBySample$evaluation_name == "eval" & eval$MetricsBySample$comparison_name == "dbsnp" & as.character(eval$MetricsBySample$jexl_expression) == "none" & eval$MetricsBySample$filter_name == "called" & eval$MetricsBySample$novelty_name == "known"),];
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metrics.novel = eval$MetricsBySample[which(eval$MetricsBySample$evaluation_name == "eval" & eval$MetricsBySample$comparison_name == "dbsnp" & as.character(eval$MetricsBySample$jexl_expression) == "none" & eval$MetricsBySample$filter_name == "called" & eval$MetricsBySample$novelty_name == "novel"),];
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title = "Calls per sample";
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indices = order(metrics.all$nVariants, decreasing=TRUE);
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plot(0, 0, type="n", xaxt="n", xlim=c(1, length(metrics.all$sample)), ylim=c(0, max(metrics.all$nVariants)), xlab="", ylab="Number of variants", main=title, bty="n");
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points(c(1:length(metrics.all$sample)), (metrics.all$nVariants)[indices], pch=21, col="black");
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points(c(1:length(metrics.known$sample)), (metrics.known$nVariants)[indices], pch=21, col="blue");
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points(c(1:length(metrics.novel$sample)), (metrics.novel$nVariants)[indices], pch=21, col="red");
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legend("topright", c("All", "Known", "Novel"), pch=21, col=c("black", "blue", "red"));
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axis(1, at=c(1:length(metrics.all$sample)), labels=(metrics.all$sample)[indices], las=2, cex.axis=0.4);
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}
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}
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plot.variantsPerSample <- function(eval, novelty_name="all") {
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if (!is.na(eval$SimpleMetricsBySample)) {
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metrics = eval$SimpleMetricsBySample[which(eval$SimpleMetricsBySample$evaluation_name == "eval" & eval$SimpleMetricsBySample$comparison_name == "dbsnp" & as.character(eval$SimpleMetricsBySample$jexl_expression) == "none" & eval$SimpleMetricsBySample$filter_name == "called" & eval$SimpleMetricsBySample$novelty_name == novelty_name),];
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title = paste("Calls per sample (", novelty_name, ")", sep="");
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indices = order(metrics$CountVariants, decreasing=TRUE);
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par.def = par(no.readonly = TRUE);
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par(mar=c(5, 4, 4, 4));
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plot(0, 0, type="n", xaxt="n", xlim=c(1, length(metrics$row)), ylim=c(0, max(metrics$CountVariants)), xlab="", ylab="Number of variants", main=title, bty="n");
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points(c(1:length(metrics$row)), (metrics$CountVariants)[indices], pch=21, col="black");
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|
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axis(1, at=c(1:length(metrics$row)), labels=(metrics$row)[indices], las=2, cex.axis=0.4);
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par(new=TRUE);
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plot(0, 0, type="n", xaxt="n", yaxt="n", xlim=c(1, length(metrics$row)), ylim=c(min(metrics$TiTvRatio), 1.2*max(metrics$TiTvRatio)), xlab="", ylab="", main=title, bty="n");
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points(c(1:length(metrics$row)), (metrics$TiTvRatio)[indices], pch=19, col="black");
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titvaxis = c(min(metrics$TiTvRatio), max(metrics$TiTvRatio));
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axis(4, at=titvaxis, labels=titvaxis, las=2);
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par(par.def);
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}
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}
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