# otherwise Linux will get into memory troubles... knitr::knit_meta("latex_dependency", clean = TRUE) knitr::opts_chunk$set( fig.width = 6, fig.height = 4, out.width = "50%" ) source(file.path(vignDir, "shared", "init.R")) runData <- T doOpt <- runData if (runData) { # try to sync with tutorial so cache can be re-used anaInfo <- patRoonData::exampleAnalysisInfo() anaInfoRG <- anaInfo anaInfoRG$group <- c(rep("repl1", 2), rep("repl2", 2), rep("repl3", 1), rep("repl4", 1)) # set max proc to 1 to limit FFM memory usage a bit on CI getFeats <- function(ai) withr::with_options(list(patRoon.multiproc.max = 1), findFeatures(ai, "openms", noiseThrInt = 2E4)) fList <- getFeats(anaInfo) fGroups <- fGroupsUF <- groupFeatures(fList, "openms") fGroups <- filter(fGroups, preAbsMinIntensity = 100, absMinIntensity = 10000, relMinReplicateAbundance = 1, maxReplicateIntRSD = 0.75, blankThreshold = 5, removeBlanks = TRUE, retentionRange = c(120, Inf), mzRange = NULL) fListRG <- getFeats(anaInfoRG) fGroupsRG <- groupFeatures(fListRG, "openms") fGroupsRG <- filter(fGroupsRG, preAbsMinIntensity = 100, absMinIntensity = 10000) anaInfoNorm <- generateAnalysisInfo(paths = patRoonData::exampleDataPath(), groups = c(rep("solvent", 3), rep("standard", 3)), blanks = "solvent", norm_concs = c(NA, NA, NA, 2, 2, 1)) fListNorm <- getFeats(anaInfoNorm) fGroupsNorm <- groupFeatures(fListNorm, "openms") fGroupsNorm <- filter(fGroupsNorm, preAbsMinIntensity = 100, absMinIntensity = 10000, relMinReplicateAbundance = 1, maxReplicateIntRSD = 0.75, blankThreshold = 5, removeBlanks = TRUE, retentionRange = c(120, Inf), mzRange = NULL) fGroupsNorm <- normInts(fGroupsNorm, featNorm = "istd", standards = patRoonData::ISTDListPos, adduct = "[M+H]+", ISTDRTWindow = 20, ISTDMZWindow = 200, minISTDs = 2) anaInfoConc <- generateAnalysisInfo(paths = patRoonData::exampleDataPath(), groups = c(rep("solvent", 3), rep("standard", 3)), blanks = "solvent", concs = c(NA, NA, NA, 1, 2, 3)) fListConc <- getFeats(anaInfoConc) fGroupsConc <- groupFeatures(fListConc, "openms") fGroupsConc <- filter(fGroupsConc, preAbsMinIntensity = 100, absMinIntensity = 10000, relMinReplicateAbundance = 1, maxReplicateIntRSD = 0.75, blankThreshold = 5, removeBlanks = TRUE, retentionRange = c(120, Inf), mzRange = NULL) fGroupsAnn <- screenSuspects(fGroups, patRoonData::suspectsPos[patRoonData::suspectsPos$name %in% c("1H-benzotriazole", "N-Phenyl urea", "2-Hydroxyquinoline", "DEET"), ], onlyHits = TRUE) avgPListParams <- getDefAvgPListParams(clusterMzWindow = 0.002) mslists <- generateMSPeakLists(fGroupsAnn, "mzr", maxMSRtWindow = 5, precursorMzWindow = 4, avgFeatParams = avgPListParams, avgFGroupParams = avgPListParams) mslists <- filter(mslists, relMSMSIntThr = 0.02, topMSMSPeaks = 10) formulas <- formsGF <- generateFormulas(fGroupsAnn, mslists, "genform", relMzDev = 5, adduct = "[M+H]+", elements = "CHNOPSCl", calculateFeatures = TRUE, featThresholdAnn = 0.75) formsSIR <- generateFormulas(fGroupsAnn, mslists, "sirius", elements = "CHNOPSCl", adduct = "[M+H]+", calculateFeatures = FALSE) compsMF <- compounds <- generateCompounds(fGroupsAnn, mslists, "metfrag", method = "CL", dbRelMzDev = 5, fragRelMzDev = 5, fragAbsMzDev = 0.002, adduct = "[M+H]+", database = "pubchemlite", maxCandidatesToStop = 5000) componCAM <- components <- generateComponents(fGroups, "camera", ionization = "positive") componInt <- generateComponents(fGroupsRG, "intclust") componNT <- generateComponents(fGroupsUF[, 1:200], "nontarget", minlength = 3, ionization = "positive") compsClust <- makeHCluster(compsMF) if (doOpt) { pSet <- generateFeatureOptPSet("openms") ftOpt <- optimizeFeatureFinding(anaInfo[1, ], "openms", pSet, maxIterations = 2, paramRanges = list(noiseThrInt = c(1500, Inf))) } fGroupsSets <- groupFeatures(makeSet(fList, getFeats(patRoonData::exampleAnalysisInfo("negative")), adducts = c("[M+H]+", "[M-H]-")), "openms") fGroupsSetsAnn <- screenSuspects(fGroupsSets, patRoonData::suspectsPos[patRoonData::suspectsPos$name == "Monuron", -2], onlyHits = TRUE) mslistsSets <- generateMSPeakLists(fGroupsSetsAnn, "mzr", maxMSRtWindow = 5, precursorMzWindow = 4, avgFeatParams = avgPListParams, avgFGroupParams = avgPListParams) mslistsSets <- filter(mslistsSets, topMSMSPeaks = 10) compoundsSets <- generateCompounds(fGroupsSetsAnn, mslistsSets, "metfrag", database = "pubchemlite") TPs <- TPsLib <- generateTPs("library", parents = patRoonData::suspectsPos) TPsBT <- generateTPs("biotransformer", parents = patRoonData::suspectsPos) fGroupsTPs <- screenSuspects(fGroups, convertToSuspects(TPsBT, includeParents = TRUE), adduct = "[M+H]+", onlyHits = TRUE) componTP <- generateComponents(fGroupsTPs, "tp", TPs = TPsBT) mslibraryMSP <- mslibrary <- loadMSLibrary(file.path(vignDir, "..", "tests", "testthat", "test_data", "MoNA-export-CASMI_2012.msp"), "msp") mslibraryJSON <- loadMSLibrary(file.path(vignDir, "..", "tests", "testthat", "test_data", "MoNA-export-CASMI_2016.json"), "json") saveRDS(list(fList = fList, fGroups = fGroups, fGroupsUF = fGroupsUF, fListRG = fListRG, fGroupsRG = fGroupsRG, fGroupsNorm = fGroupsNorm, mslists = mslists, formulas = formulas, compsMF = compsMF, componCAM = componCAM, componInt = componInt, componNT = componNT, compsClust = compsClust, ftOpt = if (doOpt) ftOpt else NULL, fGroupsSets = fGroupsSets, fGroupsSetsAnn = fGroupsSetsAnn, mslistsSets = mslistsSets, compoundsSets = compoundsSets, TPsLib = TPsLib, TPsBT = TPsBT, fGroupsTPs = fGroupsTPs, componTP = componTP), "~/handbook-obj.Rds") }
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