\name{gsa.read.eval} \alias{gsa.read.eval} \title{ Read a VariantEval file } \description{ Read a VariantEval file that's output in R format. } \usage{ gsa.read.eval(evalRoot) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{evalRoot}{ %% ~~Describe \code{evalRoot} here~~ } } \details{ %% ~~ If necessary, more details than the description above ~~ } \value{ %% ~Describe the value returned %% If it is a LIST, use %% \item{comp1 }{Description of 'comp1'} %% \item{comp2 }{Description of 'comp2'} %% ... } \references{ %% ~put references to the literature/web site here ~ } \author{ %% ~~who you are~~ } \note{ %% ~~further notes~~ } %% ~Make other sections like Warning with \section{Warning }{....} ~ \seealso{ %% ~~objects to See Also as \code{\link{help}}, ~~~ } \examples{ ##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function(evalRoot) { fileAlleleCountStats = paste(evalRoot, ".AlleleCountStats.csv", sep=""); fileCompOverlap = paste(evalRoot, ".Comp_Overlap.csv", sep=""); fileCountVariants = paste(evalRoot, ".Count_Variants.csv", sep=""); fileGenotypeConcordance = paste(evalRoot, ".Genotype_Concordance.csv", sep=""); fileMetricsByAc = paste(evalRoot, ".MetricsByAc.csv", sep=""); fileMetricsBySample = paste(evalRoot, ".MetricsBySample.csv", sep=""); fileQuality_Metrics_by_allele_count = paste(evalRoot, ".Quality_Metrics_by_allele_count.csv", sep=""); fileQualityScoreHistogram = paste(evalRoot, ".QualityScoreHistogram.csv", sep=""); fileSampleStatistics = paste(evalRoot, ".Sample_Statistics.csv", sep=""); fileSampleSummaryStatistics = paste(evalRoot, ".Sample_Summary_Statistics.csv", sep=""); fileSimpleMetricsBySample = paste(evalRoot, ".SimpleMetricsBySample.csv", sep=""); fileTi_slash_Tv_Variant_Evaluator = paste(evalRoot, ".Ti_slash_Tv_Variant_Evaluator.csv", sep=""); fileTiTvStats = paste(evalRoot, ".TiTvStats.csv", sep=""); fileVariant_Quality_Score = paste(evalRoot, ".Variant_Quality_Score.csv", sep=""); eval = list( AlleleCountStats = NA, CompOverlap = NA, CountVariants = NA, GenotypeConcordance = NA, MetricsByAc = NA, MetricsBySample = NA, Quality_Metrics_by_allele_count = NA, QualityScoreHistogram = NA, SampleStatistics = NA, SampleSummaryStatistics = NA, SimpleMetricsBySample = NA, TiTv = NA, TiTvStats = NA, Variant_Quality_Score = NA, CallsetNames = c(), CallsetOnlyNames = c(), CallsetFilteredNames = c() ); eval$AlleleCountStats = .attemptToLoadFile(fileAlleleCountStats); eval$CompOverlap = .attemptToLoadFile(fileCompOverlap); eval$CountVariants = .attemptToLoadFile(fileCountVariants); eval$GenotypeConcordance = .attemptToLoadFile(fileGenotypeConcordance); eval$MetricsByAc = .attemptToLoadFile(fileMetricsByAc); eval$MetricsBySample = .attemptToLoadFile(fileMetricsBySample); eval$Quality_Metrics_by_allele_count = .attemptToLoadFile(fileQuality_Metrics_by_allele_count); eval$QualityScoreHistogram = .attemptToLoadFile(fileQualityScoreHistogram); eval$SampleStatistics = .attemptToLoadFile(fileSampleStatistics); eval$SampleSummaryStatistics = .attemptToLoadFile(fileSampleSummaryStatistics); eval$SimpleMetricsBySample = .attemptToLoadFile(fileSimpleMetricsBySample); eval$TiTv = .attemptToLoadFile(fileTi_slash_Tv_Variant_Evaluator); eval$TiTvStats = .attemptToLoadFile(fileTiTvStats); eval$Variant_Quality_Score = .attemptToLoadFile(fileVariant_Quality_Score); uniqueJexlExpressions = unique(eval$TiTv$jexl_expression); eval$CallsetOnlyNames = as.vector(uniqueJexlExpressions[grep("FilteredIn|Intersection|none", uniqueJexlExpressions, invert=TRUE, ignore.case=TRUE)]); eval$CallsetNames = as.vector(gsub("-only", "", eval$CallsetOnlyNames)); eval$CallsetFilteredNames = as.vector(c()); eval; } } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ ~kwd1 } \keyword{ ~kwd2 }% __ONLY ONE__ keyword per line