## ----setup, echo=FALSE, results="hide"------------------------------------- # knitr::opts_chunk$set(tidy=FALSE, cache=TRUE, dev="png", message=FALSE, # error=FALSE, warning=TRUE) ## -------------------------------------------------------------------------- library(NormalyzerDE) outDir <- tempdir() designFp <- system.file(package="NormalyzerDE", "extdata", "tiny_design.tsv") dataFp <- system.file(package="NormalyzerDE", "extdata", "tiny_data.tsv") normalyzer(jobName="vignette_run", designPath=designFp, dataPath=dataFp, outputDir=outDir) ## -------------------------------------------------------------------------- normMatrixPath <- paste(outDir, "vignette_run/CycLoess-normalized.txt", sep="/") normalyzerDE("vignette_run", comparisons=c("4-5"), designPath=designFp, dataPath=normMatrixPath, outputDir=outDir, condCol="group") ## -------------------------------------------------------------------------- dataMatrix <- read.table(dataFp, sep="\t", header = TRUE) designMatrix <- read.table(designFp, sep="\t", header = TRUE) designMatrix$sample <- as.character(designMatrix$sample) dataOnly <- dataMatrix[, designMatrix$sample] annotOnly <- dataMatrix[, !(colnames(dataMatrix) %in% designMatrix$sample)] sumExpObj <- SummarizedExperiment::SummarizedExperiment( as.matrix(dataOnly), colData=designMatrix, rowData=annotOnly ) normalyzer(jobName="sumExpRun", experimentObj = sumExpObj, outputDir=outDir) ## -------------------------------------------------------------------------- fullDf <- read.csv(dataFp, sep="\t") designDf <- read.csv(designFp, sep="\t") head(fullDf, 1) head(designDf, 1) ## -------------------------------------------------------------------------- sampleNames <- as.character(designDf$sample) typeof(sampleNames) ## -------------------------------------------------------------------------- dataMat <- as.matrix(fullDf[, sampleNames]) retentionTimes <- fullDf$Average.RT head(dataMat, 1) ## -------------------------------------------------------------------------- typeof(dataMat) print("Rows and columns of data") dim(dataMat) print("Number of retention times") length(retentionTimes) ## -------------------------------------------------------------------------- performCyclicLoessNormalization <- function(rawMatrix) { log2Matrix <- log2(rawMatrix) normMatrix <- limma::normalizeCyclicLoess(log2Matrix, method="fast") colnames(normMatrix) <- colnames(rawMatrix) normMatrix } ## -------------------------------------------------------------------------- rtNormMat <- getRTNormalizedMatrix(dataMat, retentionTimes, performCyclicLoessNormalization, stepSizeMinutes=1, windowMinCount=100) ## -------------------------------------------------------------------------- globalNormMat <- performCyclicLoessNormalization(dataMat) dim(rtNormMat) dim(globalNormMat) head(rtNormMat, 1) head(globalNormMat, 1) ## -------------------------------------------------------------------------- layeredRtNormMat <- getSmoothedRTNormalizedMatrix( dataMat, retentionTimes, performCyclicLoessNormalization, stepSizeMinutes=1, windowMinCount=100, windowShifts=3, mergeMethod="mean") dim(layeredRtNormMat) head(layeredRtNormMat, 1) ## -------------------------------------------------------------------------- jobName <- "vignette_run" experimentObj <- setupRawDataObject(dataFp, designFp, "default", TRUE, "sample", "group") normObj <- getVerifiedNormalyzerObject(jobName, experimentObj) ## -------------------------------------------------------------------------- normResults <- normMethods(normObj) ## -------------------------------------------------------------------------- normResultsWithEval <- analyzeNormalizations(normResults) ## -------------------------------------------------------------------------- jobDir <- setupJobDir("vignette_run", tempdir()) writeNormalizedDatasets(normResultsWithEval, jobDir) ## -------------------------------------------------------------------------- generatePlots(normResultsWithEval, jobDir) ## -------------------------------------------------------------------------- bestNormMatPath <- paste(jobDir, "RT-Loess-normalized.txt", sep="/") experimentObj <- setupRawContrastObject(bestNormMatPath, designFp, "sample") nst <- NormalyzerStatistics(experimentObj, logTrans=FALSE) ## -------------------------------------------------------------------------- comparisons <- c("4-5") nst <- calculateContrasts(nst, comparisons, condCol="group", leastRepCount=2) ## -------------------------------------------------------------------------- annotDf <- generateAnnotatedMatrix(nst) utils::write.table(annotDf, file=paste(jobDir, "stat_table.tsv", sep="/")) generateStatsReport(nst, "Vignette stats", jobDir) ## -------------------------------------------------------------------------- sessionInfo()