## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( fig.width=7, fig.height=4.5, collapse = TRUE, eval = TRUE, comment = "#>" ) ## ----------------------------------------------------------------------------- library(ComPrAn) inputFile <- system.file("extData", "dataNormProts.txt", package = "ComPrAn") forAnalysis <- protImportForAnalysis(inputFile) ## ----------------------------------------------------------------------------- protein <- "P52815" max_frac <- 23 # example protein plot, quantitative comparison between labeled and unlabeled # samples (default settings) proteinPlot(forAnalysis[forAnalysis$scenario == "B",], protein, max_frac) ## ----groupHeatMap, fig.width=7, fig.height=6.7-------------------------------- groupDataFileName <- system.file("extData","exampleGroup.txt",package="ComPrAn") groupName <- 'group1' groupData <- data.table::fread(groupDataFileName) # example heatmap, quantitative comparison between labeled and unlabeled samples # (default settings) groupHeatMap(dataFrame = forAnalysis[forAnalysis$scenario == "B",], groupData, groupName) ## ----------------------------------------------------------------------------- groupDataVector <- c("Q16540","P52815","P09001","Q13405","Q9H2W6") groupName <- 'group1' max_frac <- 23 # example co-migration plot, non-quantitative comparison of migration profile # of a sigle protein goup between labeled and unlabeled samples # (default settings) oneGroupTwoLabelsCoMigration(forAnalysis, max_frac = max_frac, groupDataVector,groupName) ## ----------------------------------------------------------------------------- group1DataVector <- c("Q16540","P52815","P09001","Q13405","Q9H2W6") group1Name <- 'group1' group2DataVector <- c("Q9NVS2","Q9NWU5","Q9NX20","Q9NYK5","Q9NZE8") group2Name <- 'group2' max_frac <- 23 # example co-migration plot, non-quantitative comparison of migration profile # of two protein goups within label states (default settings) twoGroupsWithinLabelCoMigration(dataFrame = forAnalysis, max_frac = max_frac, group1Data = group1DataVector, group1Name = group1Name, group2Data = group2DataVector, group2Name = group2Name) ## ----------------------------------------------------------------------------- clusteringDF <- clusterComp(forAnalysis,scenar = "A", PearsCor = "centered") ## ----------------------------------------------------------------------------- labTab_clust <- assignClusters(.listDf = clusteringDF,sample = "labeled", method = 'average', cutoff = 0.85) unlabTab_clust <- assignClusters(.listDf = clusteringDF,sample = "unlabeled", method = 'average', cutoff = 0.85) ## ----clusterBar, fig.width=4, fig.height=2.5---------------------------------- makeBarPlotClusterSummary(labTab_clust, name = 'labeled') makeBarPlotClusterSummary(unlabTab_clust, name = 'unlabeled') ## ----------------------------------------------------------------------------- tableForClusterExport <- exportClusterAssignments(labTab_clust,unlabTab_clust)