Be more robust to missing or empty files in VariantEval output.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@4008 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
kiran
parent
23b5d71e76
commit
a7409df1a6
150
R/gsacommons.R
150
R/gsacommons.R
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@ -62,6 +62,16 @@ plot.venn <- function(a, b, c=0, a_and_b, a_and_c=0, b_and_c=0,
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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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@ -78,25 +88,39 @@ read.eval <- function(evalRoot) {
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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 = read.csv(fileAlleleCountStats, header=TRUE, comment.char="#"),
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CompOverlap = read.csv(fileCompOverlap, header=TRUE, comment.char="#"),
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CountVariants = read.csv(fileCountVariants, header=TRUE, comment.char="#"),
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GenotypeConcordance = read.csv(fileGenotypeConcordance, header=TRUE, comment.char="#"),
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MetricsByAc = read.csv(fileMetricsByAc, header=TRUE, comment.char="#"),
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MetricsBySample = read.csv(fileMetricsBySample, header=TRUE, comment.char="#"),
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Quality_Metrics_by_allele_count = read.csv(fileQuality_Metrics_by_allele_count, header=TRUE, comment.char="#"),
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QualityScoreHistogram = read.csv(fileQualityScoreHistogram, header=TRUE, comment.char="#"),
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SampleStatistics = read.csv(fileSampleStatistics, header=TRUE, comment.char="#"),
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SampleSummaryStatistics = read.csv(fileSampleSummaryStatistics, header=TRUE, comment.char="#"),
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TiTv = read.csv(fileTi_slash_Tv_Variant_Evaluator, header=TRUE, comment.char="#"),
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TiTvStats = read.csv(fileTiTvStats, header=TRUE, comment.char="#"),
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Variant_Quality_Score = read.csv(fileVariant_Quality_Score, header=TRUE, comment.char="#"),
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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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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$SampleSummaryStatistics = .attemptToLoadFile(fileSampleSummaryStatistics);
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eval$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$CallsetOnlyNames = as.vector(uniqueJexlExpressions[grep("Filtered|Intersection|none", uniqueJexlExpressions, invert=TRUE, ignore.case=TRUE)]);
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eval$CallsetNames = as.vector(gsub("-only", "", eval$CallsetOnlyNames));
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@ -170,34 +194,62 @@ plot.callsetConcordance <- function(eval, col=c("#FF6342", "#63C6DE", "#ADDE63")
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}
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plot.callsetConcordanceByAC <- function(eval, normalize=TRUE, novelty_name="all", col=c("#FF6342", "#5C92A4", "#55BBFF")) {
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aonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[1]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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intersection = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & eval$MetricsByAc$jexl_expression == "Intersection" & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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bonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[2]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#aonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[1]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#intersection = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & eval$MetricsByAc$jexl_expression == "Intersection" & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#bonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[2]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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aonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[1], novelty_name);
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intersection = eval.getMetricsByAc(eval, "Intersection", novelty_name);
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bonly = eval.getMetricsByAc(eval, eval$CallsetOnlyNames[2], novelty_name);
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title = paste("Callset concordance per allele count (", novelty_name, " variants)", sep="");
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if (length(intersection$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$n = 0;
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}
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if (normalize == TRUE) {
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norm = aonly$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, ylim=c(0, 1.3), border=NA);
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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, border="gray");
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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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}
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plot.alleleCountSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#5C92A4", "#55BBFF")) {
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aonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[1]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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intersection = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & eval$MetricsByAc$jexl_expression == "Intersection" & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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bonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[2]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#aonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[1]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#intersection = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & eval$MetricsByAc$jexl_expression == "Intersection" & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#bonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[2]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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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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suppressWarnings(plot(0, 0, type="n", xlim=c(1, length(intersection$n)), ylim=c(1, max(aonly$n + intersection$n, bonly$n + intersection$n)), xlab="Allele count", ylab="Number of variants", main=title, log="xy", bty="n"));
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if (length(intersection$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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@ -205,13 +257,35 @@ plot.alleleCountSpectrum <- function(eval, novelty_name="all", col=c("#FF6342",
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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$novelty_name == novelty_name),];
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}
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plot.titvSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#5C92A4", "#55BBFF")) {
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aonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[1]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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intersection = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & eval$MetricsByAc$jexl_expression == "Intersection" & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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bonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[2]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#aonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[1]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#intersection = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & eval$MetricsByAc$jexl_expression == "Intersection" & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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#bonly = eval$MetricsByAc[which(eval$MetricsByAc$evaluation_name == "eval" & eval$MetricsByAc$comparison_name == "dbsnp" & as.character(eval$MetricsByAc$jexl_expression) == as.character(eval$CallsetOnlyNames[2]) & eval$MetricsByAc$filter_name == "called" & eval$MetricsByAc$novelty_name == novelty_name),];
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aonly = eval.getMetricsByAc(eval, eval$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$nTv);
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titv.aonly.finite = titv.aonly[which(is.finite(titv.aonly))];
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@ -223,7 +297,7 @@ plot.titvSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#5C92A
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titv.min = min(titv.aonly.finite, titv.intersection.finite, titv.bonly.finite);
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titv.max = max(titv.aonly.finite, titv.intersection.finite, titv.bonly.finite);
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plot(0, 0, type="n", xlim=c(1, length(intersection$n)), ylim=c(titv.min, titv.max), xlab="Allele count", ylab="Transition/transversion (Ti/Tv) ratio", main=title, bty="n");
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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$nTv), type="l", lwd=2, col=col[3]);
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@ -238,19 +312,21 @@ plot.titvSpectrum <- function(eval, novelty_name="all", col=c("#FF6342", "#5C92A
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}
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plot.variantsPerSample <- function(eval) {
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metrics.all = eval$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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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$nVariants, decreasing=TRUE);
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title = "Calls per sample";
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indices = order(metrics.all$nVariants, decreasing=TRUE);
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plot(0, 0, type="n", xaxt="n", xlim=c(1, length(metrics$sample)), ylim=c(0, max(metrics$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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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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legend("topright", c("All", "Known", "Novel"), pch=21, col=c("black", "blue", "red"));
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axis(1, at=c(1:length(metrics$sample)), labels=(metrics$sample)[indices], las=2, cex.axis=0.4);
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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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