## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- library(msPurity) msPths <- list.files(system.file("extdata", "lcms", "mzML", package="msPurityData"), full.names = TRUE) ## ----------------------------------------------------------------------------- pa <- purityA(msPths) print(pa@puritydf[1:3,]) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- pa_norm <- purityA(msPths[3], iwNorm=TRUE, iwNormFun=iwNormGauss(sdlim=3, minOff=-0.5, maxOff=0.5)) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ ##for xcms version 3+ suppressPackageStartupMessages(library(xcms)) suppressPackageStartupMessages(library(MSnbase)) suppressPackageStartupMessages(library(magrittr)) #read in data and subset to use data between 30 and 90 seconds and 100 and 200 m/z msdata = MSnbase::readMSData(msPths, mode = 'onDisk', msLevel. = 1) rtr = c(30, 90) mzr = c(100, 200) msdata = msdata %>% MSnbase::filterRt(rt = rtr) %>% MSnbase::filterMz(mz = mzr) #perform feature detection in individual files cwp <- CentWaveParam(snthresh = 3, noise = 100, ppm = 10, peakwidth = c(3, 30)) xcmsObj <- xcms::findChromPeaks(msdata, param = cwp) #update metadata #for(i in 1:length(msPths)){ # xcmsObj@processingData@files[i] <- msPths[i] #} xcmsObj@phenoData@data$class = c('blank', 'blank', 'sample', 'sample') xcmsObj@phenoData@varMetadata = data.frame('labelDescription' = c('sampleNames', 'class')) #group chromatographic peaks across samples (correspondence analysis) pdp <- PeakDensityParam(sampleGroups = xcmsObj@phenoData@data$class, minFraction = 0, bw = 5, binSize = 0.017) xcmsObj <- groupChromPeaks(xcmsObj, param = pdp) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ pa <- frag4feature(pa = pa, xcmsObj = xcmsObj) ## ----------------------------------------------------------------------------- print(pa@grped_df[c(48,49),]) ## ----------------------------------------------------------------------------- print(pa@grped_ms2[[18]]) # fragmentation associated with the first XCMS grouped feature (i.e. xcmsObj@groups[432,] for xcms versions < 3 and featureDefinitions(xcmsObj)[432,] for xcms v3+) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ pa <- filterFragSpectra(pa) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ pa <- averageAllFragSpectra(pa) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ pa <- averageIntraFragSpectra(pa) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ pa <- averageInterFragSpectra(pa) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ td <- tempdir() createMSP(pa, msp_file_pth = file.path(td, 'out.msp')) ## ----results='hide', message=FALSE, warning=FALSE, echo = T------------------ q_dbPth <- createDatabase(pa = pa, xcmsObj = xcmsObj, outDir = td, dbName = 'test-mspurity-vignette.sqlite') ## ----------------------------------------------------------------------------- result <- spectralMatching(q_dbPth, q_xcmsGroups = c(432), cores=1, l_accessions=c('CCMSLIB00003740033')) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- msPths <- list.files(system.file("extdata", "lcms", "mzML", package="msPurityData"), full.names = TRUE, pattern = "LCMS_") ## run xcms (version 3+) # suppressPackageStartupMessages(library(xcms)) # suppressPackageStartupMessages(library(MSnbase)) # suppressPackageStartupMessages(library(magrittr)) # # #read in data and subset to use data between 30 and 90 seconds and 100 and 200 m/z # msdata = readMSData(msPths, mode = 'onDisk', msLevel. = 1) # rtr = c(30, 90) # mzr = c(100, 200) # msdata = msdata %>% MSnbase::filterRt(rt = rtr) %>% MSnbase::filterMz(mz = mzr) # # #perform feature detection in individual files # cwp <- CentWaveParam(snthresh = 3, noise = 100, ppm = 10, peakwidth = c(3, 30)) # xcmsObj <- xcms::findChromPeaks(msdata, param = cwp) # #update metadata # for(i in 1:length(msPths)){ # xcmsObj@processingData@files[i] <- msPths[i] # } # # xcmsObj@phenoData@data$class = c('sample', 'sample') # xcmsObj@phenoData@varMetadata = data.frame('labelDescription' = c('sampleNames', 'class')) # #group chromatographic peaks across samples (correspondence analysis) # pdp <- PeakDensityParam(sampleGroups = xcmsObj@phenoData@data$class, minFraction = 0, bw = 5, binSize = 0.017) # xcmsObj <- groupChromPeaks(xcmsObj, param = pdp) ## Or load an XCMS xcmsSet object saved earlier xcmsObj <- readRDS(system.file("extdata", "tests", "xcms", "ms_only_xcmsnexp.rds", package="msPurity")) ## Make sure the file paths are correct xcmsObj@processingData@files[1] = msPths[basename(msPths)=="LCMS_1.mzML"] xcmsObj@processingData@files[2] = msPths[basename(msPths)=="LCMS_2.mzML"] ## ----------------------------------------------------------------------------- px <- purityX(xset = as(xcmsObj, 'xcmsSet'), cores = 1, xgroups = c(1, 2), ilim=0) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- datapth <- system.file("extdata", "dims", "mzML", package="msPurityData") inDF <- Getfiles(datapth, pattern=".mzML", check = FALSE) ppDIMS <- purityD(inDF, mzML=TRUE) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- ppDIMS <- averageSpectra(ppDIMS, snMeth = "median", snthr = 5) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- ppDIMS <- filterp(ppDIMS, thr=5000, rsd = 10) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- detach("package:magrittr", unload=TRUE) ppDIMS <- subtract(ppDIMS) ## ----------------------------------------------------------------------------- ppDIMS <- dimsPredictPurity(ppDIMS) print(head(ppDIMS@avPeaks$processed$B02_Daph_TEST_pos)) ## ----results='hide', message=FALSE, warning=FALSE, echo = TRUE--------------- mzpth <- system.file("extdata", "dims", "mzML", "B02_Daph_TEST_pos.mzML", package="msPurityData") predicted <- dimsPredictPuritySingle(filepth = mzpth, mztargets = c(111.0436, 113.1069)) print(predicted)