## ----style, echo=FALSE, results='asis'------------------------------------- BiocStyle::markdown() ## ----setup, echo=FALSE, message=FALSE-------------------------------------- library(CardinalWorkflows) register(SerialParam()) options(Cardinal.verbose=FALSE) options(Cardinal.progress=FALSE) RNGkind("L'Ecuyer-CMRG") ## -------------------------------------------------------------------------- library(Cardinal) ## ----load-pig206----------------------------------------------------------- data(pig206, package="CardinalWorkflows") pig206 <- as(pig206, "MSImagingExperiment") ## ----show-pig206----------------------------------------------------------- pig206 ## ----mz-885---------------------------------------------------------------- image(pig206, mz=885.5, plusminus=0.25) ## ----pig206-mean----------------------------------------------------------- pig206_mean <- summarize(pig206, .stat="mean") ## ----plot-pig206-mean------------------------------------------------------ plot(pig206_mean) ## ----pig206-tic------------------------------------------------------------ pig206_tic <- summarize(pig206, .stat=c(tic="sum"), .by="pixel") ## ----plot-pig206-tic------------------------------------------------------- image(pig206_tic) ## ----peak-ref-pig206------------------------------------------------------- pig206_ref <- pig206_mean %>% peakPick(SNR=3) %>% peakAlign(ref="mean", tolerance=0.5, units="mz") %>% peakFilter() %>% process() ## ----peak-bin-pig206------------------------------------------------------- pig206_peaks <- pig206 %>% normalize(method="tic") %>% peakBin(ref=mz(pig206_ref), tolerance=0.5, units="mz") %>% process() pig206_peaks ## ----mz-187---------------------------------------------------------------- image(pig206_peaks, mz=187) ## ----mz-840---------------------------------------------------------------- image(pig206_peaks, mz=840) ## ----mz-537---------------------------------------------------------------- image(pig206_peaks, mz=537) ## -------------------------------------------------------------------------- pig206_pca <- PCA(pig206_peaks, ncomp=3) ## -------------------------------------------------------------------------- image(pig206_pca, contrast.enhance="histogram", normalize.image="linear") ## -------------------------------------------------------------------------- plot(pig206_pca, lwd=2) ## ----ssc------------------------------------------------------------------- set.seed(1) pig206_ssc <- spatialShrunkenCentroids(pig206_peaks, method="adaptive", r=2, s=c(0,5,10,15,20,25), k=10) ## ----show-ssc-------------------------------------------------------------- summary(pig206_ssc) ## ----ssc-image-multi------------------------------------------------------- image(pig206_ssc, model=list(s=c(10,15,20,25))) ## ----ssc-image-s20--------------------------------------------------------- image(pig206_ssc, model=list(s=20)) ## ----ssc-centers----------------------------------------------------------- plot(pig206_ssc, model=list(s=20), lwd=2) ## ----ssc-centers-2--------------------------------------------------------- cols <- discrete.colors(6) setup.layout(c(3,1)) plot(pig206_ssc, model=list(s=20), column=1, col=cols[1], lwd=2, layout=NULL) plot(pig206_ssc, model=list(s=20), column=5, col=cols[5], lwd=2, layout=NULL) plot(pig206_ssc, model=list(s=20), column=6, col=cols[6], lwd=2, layout=NULL) ## ----ssc-statistic--------------------------------------------------------- plot(pig206_ssc, model=list(s=20), values="statistic", lwd=2) ## ----ssc-statistic-2------------------------------------------------------- setup.layout(c(3,1)) plot(pig206_ssc, model=list(s=20), values="statistic", column=1, col=cols[1], lwd=2, layout=NULL) plot(pig206_ssc, model=list(s=20), values="statistic", column=5, col=cols[5], lwd=2, layout=NULL) plot(pig206_ssc, model=list(s=20), values="statistic", column=6, col=cols[6], lwd=2, layout=NULL) ## ----top-heart------------------------------------------------------------- topFeatures(pig206_ssc, model=list(s=20), class==1) ## ----top-brain------------------------------------------------------------- topFeatures(pig206_ssc, model=list(s=20), class==5) ## ----top-liver------------------------------------------------------------- topFeatures(pig206_ssc, model=list(s=20), class==6) ## ----load-cardinal--------------------------------------------------------- data(cardinal, package="CardinalWorkflows") cardinal <- as(cardinal, "MSImagingExperiment") ## ----show-cardinal--------------------------------------------------------- cardinal ## ----cardinal-mean--------------------------------------------------------- cardinal_mean <- summarize(cardinal, .stat="mean") ## ----peak-ref-cardinal----------------------------------------------------- cardinal_ref <- cardinal_mean %>% peakPick(SNR=3) %>% peakAlign(ref="mean", tolerance=0.5, units="mz") %>% peakFilter() %>% process() ## ----peak-bin-cardinal----------------------------------------------------- cardinal_peaks <- cardinal %>% normalize(method="tic") %>% peakBin(ref=mz(cardinal_ref), tolerance=0.5, units="mz") %>% process() cardinal_peaks ## ----ssc-cardinal---------------------------------------------------------- set.seed(1) cardinal_ssc <- spatialShrunkenCentroids(cardinal_peaks, method="adaptive", r=2, s=c(10,20,30,40), k=10) ## ----show-ssc-cardinal----------------------------------------------------- summary(cardinal_ssc) ## ----ssc-cardinal-multi---------------------------------------------------- image(cardinal_ssc) ## ----ssc-cardinal-image---------------------------------------------------- image(cardinal_ssc, model=list(s=40), col=c("1"=NA, "2"="gray", "3"="black", "4"="firebrick", "5"="brown", "6"="darkred", "7"="red")) ## ----top-body-------------------------------------------------------------- topFeatures(cardinal_ssc, model=list(s=40), class==7) image(cardinal, mz=207) ## ----top-text-------------------------------------------------------------- topFeatures(cardinal_ssc, model=list(s=40), class==3) image(cardinal, mz=649) ## ----session-info---------------------------------------------------------- sessionInfo()