437 lines
24 KiB
R
437 lines
24 KiB
R
suppressPackageStartupMessages(library(gsalib));
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suppressPackageStartupMessages(library(gplots));
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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: %0.2f\nKnown: %d, Ti/Tv: %0.2f\nNovel: %d, Ti/Tv: %0.2f",
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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, filtered in %s:\nAll: %d, Ti/Tv: %0.2f\nKnown: %d, Ti/Tv: %0.2f\nNovel: %d, Ti/Tv: %0.2f\n\nCalled in %s, absent in %s:\nAll: %d, Ti/Tv: %0.2f\nKnown: %d, Ti/Tv: %0.2f\nNovel: %d, Ti/Tv: %0.2f",
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name, 100*(metrics$all + filtered.metrics$all)/union$all.withfiltered,
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name, othername,
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filtered.metrics$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$novel.titv,
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name, othername,
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metrics$all, metrics$all.titv,
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metrics$known, metrics$known.titv,
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metrics$novel, metrics$novel.titv
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);
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}
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}
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plot.titlePage <- function(title, author) {
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textplot(sprintf("Automated Variant Report\n\n%s\n%s\n%s\n", title, author, Sys.Date()));
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}
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.plot.variantTable.getRowText <- function(eval, jexl_expression) {
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allVariants = eval$CountVariants[which(eval$CountVariants$jexl_expression == jexl_expression & eval$CountVariants$filter_name == "called" & eval$CountVariants$novelty_name == "all"),]$nVariantLoci;
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knownVariants = eval$CountVariants[which(eval$CountVariants$jexl_expression == jexl_expression & eval$CountVariants$filter_name == "called" & eval$CountVariants$novelty_name == "known"),]$nVariantLoci;
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novelVariants = eval$CountVariants[which(eval$CountVariants$jexl_expression == jexl_expression & eval$CountVariants$filter_name == "called" & eval$CountVariants$novelty_name == "novel"),]$nVariantLoci;
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allTiTv = eval$TiTv[which(eval$TiTv$jexl_expression == jexl_expression & eval$TiTv$filter_name == "called" & eval$TiTv$novelty_name == "all"),]$ti.tv_ratio;
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knownTiTv = eval$TiTv[which(eval$TiTv$jexl_expression == jexl_expression & eval$TiTv$filter_name == "called" & eval$TiTv$novelty_name == "known"),]$ti.tv_ratio;
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novelTiTv = eval$TiTv[which(eval$TiTv$jexl_expression == jexl_expression & eval$TiTv$filter_name == "called" & eval$TiTv$novelty_name == "novel"),]$ti.tv_ratio;
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cbind(allVariants, knownVariants, sprintf("%0.2f", knownTiTv), novelVariants, sprintf("%0.2f", novelTiTv));
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}
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plot.variantTable <- function(eval, title) {
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aonly.row = .plot.variantTable.getRowText(eval, eval$CallsetOnlyNames[1]);
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aonly.filtered.row = .plot.variantTable.getRowText(eval, eval$CallsetFilteredNames[1]);
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intersection.row = .plot.variantTable.getRowText(eval, "Intersection");
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bonly.row = .plot.variantTable.getRowText(eval, eval$CallsetOnlyNames[2]);
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bonly.filtered.row = .plot.variantTable.getRowText(eval, eval$CallsetFilteredNames[2]);
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variantsummary = as.data.frame(rbind(bonly.row, bonly.filtered.row, intersection.row, aonly.filtered.row, aonly.row));
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rownames(variantsummary) = c(
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sprintf("Called in %s, absent in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
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sprintf("Called in %s, filtered in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
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"Intersection",
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sprintf("Called in %s, filtered in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2]),
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sprintf("Called in %s, absent in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2])
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);
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colnames(variantsummary) = c("counts (all)", "counts (known)", "ti/tv (known)", "counts (novel)", "ti/tv (novel)");
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textplot(variantsummary);
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}
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plot.callsetConcordance <- function(eval, col=c("#FF6342", "#63C6DE", "#ADDE63")) {
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aonly = eval.getMetrics(eval, eval$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$all
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);
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gsa.plot.venn(aonly$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", "#FF9675", "#5C92A4", "#88EEFF", "#55BBFF")) {
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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aonly.filtered = eval.getMetricsByAc(eval, eval$CallsetFilteredNames[1]);
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intersection = eval.getMetricsByAc(eval, "Intersection", novelty_name);
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bonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[2], novelty_name);
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bonly.filtered = eval.getMetricsByAc(eval, eval$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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if (length(intersection$AC) > 0 && length(aonly.filtered$AC) == 0) {
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aonly.filtered = intersection;
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aonly.filtered$n = 0;
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}
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if (length(intersection$AC) > 0 && length(bonly.filtered$AC) == 0) {
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bonly.filtered = intersection;
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bonly.filtered$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$n + aonly.filtered$n + intersection$n + bonly$n + bonly.filtered$n;
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matnorm = rbind(aonly$n/norm, aonly.filtered$n/norm, intersection$n/norm, bonly.filtered$n/norm, bonly$n/norm);
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barplot(matnorm, col=col, xlab="Allele count", ylab="", main=title, names.arg=intersection$AC, xlim=c(1, 1.2*max(intersection$AC)), ylim=c(0, 1.3), border=NA, yaxt="n", cex=1.3, cex.axis=1.3, cex.lab=1.3);
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axis(2, at=seq(from=0, to=1, by=0.2), seq(from=0, to=1, by=0.2), cex=1.3, cex.axis=1.3);
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mtext("Fraction", side=2, at=0.5, padj=-3.0, cex=1.3);
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} else {
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mat = rbind(aonly$n, aonly.filtered$n, intersection$n, bonly.filtered$n, bonly$n);
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#barplot(mat, col=col, xlab="Allele count", ylab="counts", main=title, names.arg=intersection$AC, xlim=c(1, max(intersection$AC)), ylim=c(0, 1), border=NA, cex=1.3, cex.axis=1.3, cex.lab=1.3);
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barplot(mat, col=col, xlab="Allele count", ylab="counts", main=title, names.arg=intersection$AC, xlim=c(1, 1.2*max(intersection$AC)), border=NA, cex=1.3, cex.axis=1.3, cex.lab=1.3);
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#axis(2, at=seq(from=0, to=1, by=0.2), seq(from=0, to=1, by=0.2), cex=1.3, cex.axis=1.3);
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#mtext("Fraction", side=2, at=0.5, padj=-3.0, cex=1.3);
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}
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legend(
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"topright",
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c(
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sprintf("Called in %s, absent in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
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sprintf("Called in %s, filtered in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
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"Intersection",
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sprintf("Called in %s, filtered in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2]),
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sprintf("Called in %s, absent in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2])
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),
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fill=rev(col),
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cex=1.3
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);
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#par(par.def);
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}
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plot.alleleCountSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#FF9675", "#5C92A4", "#88EEFF", "#55BBFF")) {
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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aonly.filtered = eval.getMetricsByAc(eval, eval$CallsetFilteredNames[1]);
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intersection = eval.getMetricsByAc(eval, "Intersection", novelty_name);
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intersection.all = eval.getMetrics(eval, "Intersection");
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bonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[2], novelty_name);
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bonly.filtered = eval.getMetricsByAc(eval, eval$CallsetFilteredNames[2]);
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title = paste("Allele count spectrum (", novelty_name, " variants)", sep="");
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if (length(intersection$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$n = 0;
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}
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if (length(intersection$AC) > 0 && length(aonly.filtered$AC) == 0) {
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aonly.filtered = intersection;
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aonly.filtered$n = 0;
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}
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if (length(intersection$AC) > 0 && length(bonly.filtered$AC) == 0) {
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bonly.filtered = intersection;
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bonly.filtered$n = 0;
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}
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loci = (unique(eval$CountVariants$nProcessedLoci))[1];
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ymax = 10*max((1/1000)*loci*(1/c(1:max(intersection$AC))));
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suppressWarnings(plot(0, 0, type="n", xlim=c(1, length(intersection$AC)), ylim=c(1, ymax), xlab="Allele count", ylab="Number of variants", main=title, log="xy", bty="n", cex=1.3, cex.lab=1.3, cex.axis=1.3));
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suppressWarnings(points(intersection$AC, aonly$n + aonly.filtered$n + intersection$n, type="l", lwd=2, col=col[1]));
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suppressWarnings(points(intersection$AC, aonly$n + intersection$n, type="l", lwd=2, lty=2, col=col[1]));
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suppressWarnings(points(intersection$AC, intersection$n, type="l", lwd=2, col=col[3]));
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suppressWarnings(points(intersection$AC, bonly$n + intersection$n, type="l", lwd=2, lty=2, col=col[4]));
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suppressWarnings(points(intersection$AC, bonly$n + bonly.filtered$n + intersection$n, type="l", lwd=2, col=col[5]));
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#points(c(1:max(intersection$AC)), 0.9*(1/1000)*loci*(1/c(1:max(intersection$AC))), type="l", lwd=2, lty=2, col="black");
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legend(
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"bottomleft",
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c(
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sprintf("Intersection + called in %s, absent or filtered in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
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sprintf("Intersection + called in %s, absent in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
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"Intersection",
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sprintf("Intersection + called in %s, absent in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2]),
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sprintf("Intersection + called in %s, absent or filtered in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2])#,
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#sprintf("Neutral expectation ( 0.9*(1/1000)*%0.1f*(1/c(1:max(%d))) )", loci, max(intersection$AC))
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),
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lwd=c(2, 2, 3, 2, 2, 2),
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lty=c(1, 2, 1, 2, 1, 2),
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col=c(rev(col), "black"),
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cex=1.3
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);
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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$novelty_name == novelty_name),];
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}
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plot.titvSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#FF9675", "#5C92A4", "#88EEFF", "#55BBFF")) {
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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aonly.filtered = eval.getMetricsByAc(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.getMetricsByAc(eval, eval$CallsetFilteredNames[2]);
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title = paste("Ti/Tv spectrum (", novelty_name, " variants)", sep="");
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if (length(intersection$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$nTv = 0;
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}
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if (length(intersection$AC) > 0 && length(aonly.filtered$AC) == 0) {
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aonly.filtered = intersection;
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aonly.filtered$n = 0;
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aonly.filtered$nTi = 0;
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aonly.filtered$nTv = 0;
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}
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if (length(intersection$AC) > 0 && length(bonly.filtered$AC) == 0) {
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bonly.filtered = intersection;
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bonly.filtered$n = 0;
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bonly.filtered$nTi = 0;
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bonly.filtered$nTv = 0;
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}
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titv.aonly.withfiltered = (aonly$nTi + aonly.filtered$nTi + intersection$nTi)/(aonly$nTv + aonly.filtered$nTv + intersection$nTv);
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titv.aonly.withfiltered.finite = titv.aonly.withfiltered[which(is.finite(titv.aonly.withfiltered))];
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titv.aonly = (aonly$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$nTv);
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titv.bonly.finite = titv.bonly[which(is.finite(titv.bonly))];
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titv.bonly.withfiltered = (bonly$nTi + bonly.filtered$nTi + intersection$nTi)/(bonly$nTv + bonly.filtered$nTv + intersection$nTv);
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titv.bonly.withfiltered.finite = titv.bonly.withfiltered[which(is.finite(titv.bonly.withfiltered))];
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titv.min = min(titv.aonly.withfiltered.finite, titv.aonly.finite, titv.intersection.finite, titv.bonly.finite, titv.bonly.withfiltered.finite);
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titv.max = max(titv.aonly.withfiltered.finite, titv.aonly.finite, titv.intersection.finite, titv.bonly.finite, titv.bonly.withfiltered.finite);
|
|
|
|
plot(0, 0, type="n", xlim=c(1, length(intersection$AC)), ylim=c(0, 4), xlab="Allele count", ylab="Transition/transversion (Ti/Tv) ratio", main=title, bty="n", cex=1.3, cex.lab=1.3, cex.axis=1.3);
|
|
points(intersection$AC, (aonly.filtered$nTi + intersection$nTi)/(aonly.filtered$nTv + intersection$nTv), type="l", lwd=2, col=col[1]);
|
|
points(intersection$AC, (aonly$nTi + intersection$nTi)/(aonly$nTv + intersection$nTv), type="l", lwd=2, lty=2, col=col[2]);
|
|
points(intersection$AC, intersection$Ti.Tv, type="l", lwd=2, col=col[3]);
|
|
points(intersection$AC, (bonly$nTi + intersection$nTi)/(bonly$nTv + intersection$nTv), type="l", lwd=2, lty=2, col=col[4]);
|
|
points(intersection$AC, (bonly.filtered$nTi + intersection$nTi)/(bonly.filtered$nTv + intersection$nTv), type="l", lwd=2, col=col[5]);
|
|
|
|
abline(h=2.3, lty=2);
|
|
mtext("2.3", side=4, at=2.3, cex=0.9);
|
|
|
|
abline(h=3.3, lty=2);
|
|
mtext("3.3", side=4, at=3.3, cex=0.9);
|
|
|
|
#legend("topleft", c(eval$CallsetOnlyNames[1], "Intersection", eval$CallsetOnlyNames[2]), fill=col);
|
|
|
|
legend(
|
|
"topleft",
|
|
c(
|
|
sprintf("Intersection + called in %s, absent or filtered in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
|
|
sprintf("Intersection + called in %s, absent in %s", eval$CallsetOnlyNames[2], eval$CallsetOnlyNames[1]),
|
|
"Intersection",
|
|
sprintf("Intersection + called in %s, absent in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2]),
|
|
sprintf("Intersection + called in %s, absent or filtered in %s", eval$CallsetOnlyNames[1], eval$CallsetOnlyNames[2])
|
|
),
|
|
lwd=c(2, 2, 3, 2, 2),
|
|
lty=c(1, 2, 1, 2, 1),
|
|
col=rev(col),
|
|
cex=1.3
|
|
);
|
|
}
|
|
|
|
plot.variantsPerSample2 <- function(eval) {
|
|
if (!is.na(eval$MetricsBySample)) {
|
|
metrics.all = eval$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"),];
|
|
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$novelty_name == "known"),];
|
|
metrics.novel = eval$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"),];
|
|
|
|
title = "Calls per sample";
|
|
indices = order(metrics.all$nVariants, decreasing=TRUE);
|
|
|
|
plot(0, 0, type="n", xaxt="n", xlim=c(1, length(metrics.all$sample)), ylim=c(0, max(metrics.all$nVariants)), xlab="", ylab="Number of variants", main=title, bty="n");
|
|
points(c(1:length(metrics.all$sample)), (metrics.all$nVariants)[indices], pch=21, col="black");
|
|
points(c(1:length(metrics.known$sample)), (metrics.known$nVariants)[indices], pch=21, col="blue");
|
|
points(c(1:length(metrics.novel$sample)), (metrics.novel$nVariants)[indices], pch=21, col="red");
|
|
|
|
legend("topright", c("All", "Known", "Novel"), pch=21, col=c("black", "blue", "red"));
|
|
|
|
axis(1, at=c(1:length(metrics.all$sample)), labels=(metrics.all$sample)[indices], las=2, cex.axis=0.4);
|
|
}
|
|
}
|
|
|
|
plot.variantsPerSample <- function(eval, novelty_name="all") {
|
|
if (!is.na(eval$SimpleMetricsBySample)) {
|
|
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$novelty_name == novelty_name),];
|
|
|
|
title = paste("Calls per sample (", novelty_name, ")", sep="");
|
|
indices = order(metrics$CountVariants, decreasing=TRUE);
|
|
|
|
par.def = par(no.readonly = TRUE);
|
|
par(mar=c(5, 4, 4, 4));
|
|
|
|
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");
|
|
points(c(1:length(metrics$row)), (metrics$CountVariants)[indices], pch=21, col="black");
|
|
|
|
axis(1, at=c(1:length(metrics$row)), labels=(metrics$row)[indices], las=2, cex.axis=0.4);
|
|
|
|
par(new=TRUE);
|
|
plot(0, 0, type="n", xaxt="n", yaxt="n", xlim=c(1, length(metrics$row)), ylim=c(min(metrics$TiTvRatio), 1.2*max(metrics$TiTvRatio)), xlab="", ylab="", main=title, bty="n");
|
|
points(c(1:length(metrics$row)), (metrics$TiTvRatio)[indices], pch=19, col="black");
|
|
|
|
titvaxis = c(min(metrics$TiTvRatio), max(metrics$TiTvRatio));
|
|
axis(4, at=titvaxis, labels=titvaxis, las=2);
|
|
|
|
par(par.def);
|
|
}
|
|
}
|
|
|
|
argspec = list(
|
|
evalRoot = list(value = NA, doc = "Path to the VariantEval R-output (omit the '.Analysis_Type.csv' part of the filename)"),
|
|
plotOut = list(value = NA, doc = "Path to the output PDF file"),
|
|
title = list(value = NA, doc = "The title of the report"),
|
|
author = list(value = NA, doc = "The author of the report")
|
|
);
|
|
|
|
cmdargs = gsa.getargs(argspec, doc="Take VariantEval R-output and generate a series of plots summarizing the contents");
|
|
|
|
eval = gsa.read.eval(cmdargs$evalRoot);
|
|
|
|
pdf(cmdargs$plotOut, width=10, height=10);
|
|
|
|
plot.titlePage(cmdargs$title, cmdargs$author);
|
|
|
|
plot.variantTable(eval);
|
|
|
|
if (length(eval$CallsetNames) > 0) {
|
|
# Venn diagram
|
|
plot.callsetConcordance(eval);
|
|
|
|
# Venn by AC (normalized)
|
|
plot.callsetConcordanceByAC(eval, novelty_name="all");
|
|
plot.callsetConcordanceByAC(eval, novelty_name="known");
|
|
plot.callsetConcordanceByAC(eval, novelty_name="novel");
|
|
|
|
# Venn by AC (unnormalized)
|
|
plot.callsetConcordanceByAC(eval, novelty_name="all", normalize=FALSE);
|
|
plot.callsetConcordanceByAC(eval, novelty_name="known", normalize=FALSE);
|
|
plot.callsetConcordanceByAC(eval, novelty_name="novel", normalize=FALSE);
|
|
|
|
# Allele count spectrum
|
|
plot.alleleCountSpectrum(eval, novelty_name="all");
|
|
plot.alleleCountSpectrum(eval, novelty_name="known");
|
|
plot.alleleCountSpectrum(eval, novelty_name="novel");
|
|
|
|
# Ti/Tv spectrum
|
|
plot.titvSpectrum(eval, novelty_name="all");
|
|
plot.titvSpectrum(eval, novelty_name="known");
|
|
plot.titvSpectrum(eval, novelty_name="novel");
|
|
|
|
# Per-sample
|
|
#plot.variantsPerSample(eval);
|
|
} else {
|
|
#plot.variantsPerSample(eval, novelty_name="all");
|
|
#plot.variantsPerSample(eval, novelty_name="known");
|
|
#plot.variantsPerSample(eval, novelty_name="novel");
|
|
}
|
|
|
|
dev.off();
|