## ----global_options, include=FALSE--------------------------------------- knitr::opts_chunk$set(fig.width=3.5, fig.height=3.5, fig.path='Figs/', echo=TRUE, warning=FALSE, message=FALSE) ## ---- message=FALSE------------------------------------------------------ library(tofsims) library(tofsimsData) ### get path to raw data file rawData<-system.file('rawdata', 'trift_test_001.RAW', package="tofsimsData") ### the following param will cause to run non parallel library(BiocParallel) register(SnowParam(workers=0), default=TRUE) spectraImport<-MassSpectra(select = 'ulvacraw', analysisName = rawData) ## ------------------------------------------------------------------------ show(spectraImport) plot(spectraImport, mzRange=c(1,150), type='l') ## ---- message=FALSE------------------------------------------------------ spectraImport <- calibPointNew(object = spectraImport, mz = 15, value = 15.0113) spectraImport <- calibPointNew(object = spectraImport, mz = 181, value = 181.0444) spectraImport <- recalibrate(spectraImport) ## ---- tidy=FALSE, message=FALSE------------------------------------------ spectraImport <- unitMassPeaks(object = spectraImport, mzRange = c(1,250), widthAt = c(15,181), factor = c(0.4, 0.6), lower = c(14.96283,15.05096), upper = c(180.80902,181.43538)) plot(spectraImport, mzRange=c(35,45), type='l') ## ------------------------------------------------------------------------ library(RColorBrewer) imageImport<-MassImage(select = 'ulvacrawpeaks', analysisName = rawData, PeakListobj = spectraImport) imageImport <- poissonScaling(imageImport) image(imageImport, col=brewer.pal(9, 'PuRd')) ## ---- fig.width=7, fig.height=2, results="hide"-------------------------- imageImport <- PCAnalysis(imageImport, nComp = 4) imageImport <- MAF(imageImport, nComp = 4) par(mar=c(0,0,0,0), oma=c(0,0,0,0), mfrow=c(2,4)) for(iii in 1:4) image(analysis(imageImport, 1), comp=iii) for(iii in 1:4) image(analysis(imageImport, 2), comp=iii) ## ---- fig.width=3.5, fig.height=3.5-------------------------------------- library(EBImage) pcaScore3<-imageMatrix(analysis(imageImport, 1), comp=3) pcaScore3Mask<-thresh(x = pcaScore3, h = 30, w = 30) par(mar=c(0,0,0,0), oma=c(0,0,0,0)) image(pcaScore3Mask, col=c('white', 'black')) ## ------------------------------------------------------------------------ paste(round(100/(xy(imageImport)[1]*xy(imageImport)[2])*sum(pcaScore3Mask),2), ' % of the image is Cell Wall') ## ---- fig.width=7, fig.height=3.5---------------------------------------- opened<-opening(pcaScore3Mask, kern = makeBrush(3, shape = 'diamond')) closed<-closing(pcaScore3Mask, kern = makeBrush(3, shape = 'diamond')) par(mar=c(0,0,0,0), oma=c(0,0,0,0), mfcol=c(1,2)) image(opened, col = c('white', 'black')) image(closed, col = c('white','black')) ## ---- fig.width=7, fig.height=3.5---------------------------------------- cellWall<-bwApply(imageImport,(opened-1)^2) par(mar=c(0,0,0,0), oma=c(0,0,0,0), mfcol=c(1,2)) image(cellWall,col=brewer.pal(9, 'PuRd')) image(imageImport,col=brewer.pal(9, 'PuRd'))