## ----style-knitr, eval=TRUE, echo=FALSE, results='asis'-------------------- BiocStyle::latex() ## ----opts, include=FALSE, echo=FALSE--------------------------------------- knitr::opts_chunk$set(concordance=TRUE, eval = TRUE, cache = TRUE, resize.width="0.45\\textwidth", fig.align='center', tidy = FALSE, message=FALSE) ## ----install, eval=FALSE--------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)){ # install.packages("BiocManager") # } # BiocManager::install("TPP") ## ----package--------------------------------------------------------------- library("TPP") ## ----load_tr_data---------------------------------------------------------- data("hdacTR_smallExample") ls() ## ----locate_example_data--------------------------------------------------- system.file('example_data', package = 'TPP') ## ----tr_config_table------------------------------------------------------- print(hdacTR_config) ## ----dataSummaryTP--------------------------------------------------------- summary(hdacTR_data) ## ----dataStatsTP----------------------------------------------------------- data.frame(Proteins = sapply(hdacTR_data, nrow)) ## ----datahead-------------------------------------------------------------- hdacVehicle1 <- hdacTR_data[["Vehicle_1"]] head(hdacVehicle1) ## ----result_path_TR-------------------------------------------------------- resultPath = file.path(getwd(), 'Panobinostat_Vignette_Example') ## ----analyzeTR------------------------------------------------------------- TRresults <- analyzeTPPTR(configTable = hdacTR_config, methods = "meltcurvefit", data = hdacTR_data, nCores = 2, resultPath = resultPath, plotCurves = FALSE) ## ----trTargets------------------------------------------------------------- tr_targets <- subset(TRresults, fulfills_all_4_requirements)$Protein_ID print(tr_targets) ## ----trHDACTargets--------------------------------------------------------- hdac_targets <- grep("HDAC", tr_targets, value=TRUE) print(hdac_targets) ## ----trImport, message=TRUE------------------------------------------------ trData <- tpptrImport(configTable = hdacTR_config, data = hdacTR_data) ## ----trData_vehicle1------------------------------------------------------- trData[["Vehicle_1"]] ## ----trDefaultNormReqs----------------------------------------------------- print(tpptrDefaultNormReqs()) ## ----trNormalization, message = TRUE--------------------------------------- normResults <- tpptrNormalize(data=trData) trDataNormalized <- normResults[["normData"]] ## ----trSelectHDACs--------------------------------------------------------- trDataHDAC <- lapply(trDataNormalized, function(d) d[Biobase::featureNames(d) %in% hdac_targets,]) ## ----trFitHDAC, message = TRUE--------------------------------------------- trDataHDAC <- tpptrCurveFit(data = trDataHDAC, resultPath = resultPath, nCores = 1) ## ----fittedMeltPars-------------------------------------------------------- Biobase::pData(Biobase::featureData(trDataHDAC[["Vehicle_1"]]))[,1:5] ## ----loadTRfitResultss----------------------------------------------------- load(file.path(resultPath, "dataObj", "fittedData.RData"), verbose=TRUE) ## ----trPvals, message=TRUE, cache=TRUE------------------------------------- minR2New <- 0.5 # instead of 0.8 maxPlateauNew <- 0.7 # instead of 0.3 newFilters <- list(minR2 = minR2New, maxPlateau = maxPlateauNew) TRresultsNew <- tpptrAnalyzeMeltingCurves(data = trDataFitted, pValFilter = newFilters) ## ----compBWidth------------------------------------------------------------ tr_targetsNew <- subset(TRresultsNew, fulfills_all_4_requirements)$Protein_ID targetsGained <- setdiff(tr_targetsNew, tr_targets) targetsLost <- setdiff(tr_targets, tr_targetsNew) print(targetsGained) print(targetsLost) ## ----nparcVignette, eval = FALSE------------------------------------------- # browseVignettes("TPP") ## ----trExport, message=TRUE, eval=FALSE------------------------------------ # tppExport(tab = TRresultsNew, # file = file.path(resultPath, "targets_newFilters.xlsx")) ## ----newNormReqs----------------------------------------------------------- trNewReqs <- tpptrDefaultNormReqs() print(trNewReqs) trNewReqs$otherRequirements[1,"colName"] <- "mycolName" trNewReqs$fcRequirements[,"fcColumn"] <- c(6,8,9) print(trNewReqs) ## ----load_ccr_data--------------------------------------------------------- data("hdacCCR_smallExample") ## ----analyzeCCR, cache=TRUE------------------------------------------------ CCRresults <- analyzeTPPCCR(configTable = hdacCCR_config[1,], data = hdacCCR_data[[1]], resultPath = resultPath, plotCurves = FALSE, nCores = 2) ## ----ccrTargets------------------------------------------------------------ ccr_targets <- subset(CCRresults, passed_filter_Panobinostat_1)$Protein_ID print(ccr_targets) ## ----ccrHDACTargets-------------------------------------------------------- hdac_targets <- grep("HDAC", ccr_targets, value = TRUE) print(hdac_targets) ## ----ccrImport, message=TRUE----------------------------------------------- ccrData <- tppccrImport(configTable = hdacCCR_config[1,], data = hdacCCR_data[[1]]) ## ----ccrNormalization, message=TRUE---------------------------------------- ccrDataNormalized <- tppccrNormalize(data = ccrData) ## ----ccrTransform, message=TRUE-------------------------------------------- ccrDataTransformed <- tppccrTransform(data = ccrDataNormalized)[[1]] ## ----ccrSelectHDACs-------------------------------------------------------- ccrDataHDAC <- ccrDataTransformed[match(hdac_targets, Biobase::featureNames(ccrDataTransformed)),] ## ----ccrFitHDAC, message=TRUE, cache=TRUE---------------------------------- ccrDataFittedHDAC <- tppccrCurveFit(data=list(Panobinostat_1 = ccrDataHDAC), nCores = 1) tppccrPlotCurves(ccrDataFittedHDAC, resultPath = resultPath, nCores = 1) ## ----fittedDRPars---------------------------------------------------------- ccrResultsHDAC <- tppccrResultTable(ccrDataFittedHDAC) print(ccrResultsHDAC[,c(1, 22:25)])