112 lines
4.4 KiB
Plaintext
112 lines
4.4 KiB
Plaintext
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\name{gsa.read.eval}
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\alias{gsa.read.eval}
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\title{
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Read a VariantEval file
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}
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\description{
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Read a VariantEval file that's output in R format.
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}
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\usage{
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gsa.read.eval(evalRoot)
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}
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%- maybe also 'usage' for other objects documented here.
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\arguments{
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\item{evalRoot}{
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%% ~~Describe \code{evalRoot} here~~
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}
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}
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\details{
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%% ~~ If necessary, more details than the description above ~~
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}
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\value{
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%% ~Describe the value returned
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%% If it is a LIST, use
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%% \item{comp1 }{Description of 'comp1'}
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%% \item{comp2 }{Description of 'comp2'}
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%% ...
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}
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\references{
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%% ~put references to the literature/web site here ~
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}
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\author{
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%% ~~who you are~~
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}
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\note{
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%% ~~further notes~~
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}
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%% ~Make other sections like Warning with \section{Warning }{....} ~
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\seealso{
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%% ~~objects to See Also as \code{\link{help}}, ~~~
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}
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\examples{
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##---- Should be DIRECTLY executable !! ----
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##-- ==> Define data, use random,
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##-- or do help(data=index) for the standard data sets.
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## The function is currently defined as
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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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eval;
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}
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}
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% Add one or more standard keywords, see file 'KEYWORDS' in the
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% R documentation directory.
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\keyword{ ~kwd1 }
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\keyword{ ~kwd2 }% __ONLY ONE__ keyword per line
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