In protViz/SRMService: Report Quantitative Mass Spectrometry Data

knitr::opts_chunk$set(echo = FALSE, fig.width = 7, fig.height = 7)

R Markdown

library(pROC)
library(plyr)
library(ggplot2)
library(ggrepel)

tdatalog2<-t( protData$getIntensities() )
Ucond <- unique(protData$getWideFormat()$Condition)
iidx <- grep(Ucond[1], protData$getWideFormat()$Condition)
jidx <- grep(Ucond[2], protData$getWideFormat()$Condition)
tvals <- getTValuesForVolcano(tdatalog2[,iidx], tdatalog2[,jidx] )

res <- data.frame(comparison = paste(Ucond[1],"_", Ucond[2],sep=""),
                                   label = rownames(tdatalog2),
                                   pvals=tvals$pval ,
                                   foldchange=tvals$fchange,
                                   pvals.adj = tvals$pvaladj )

#quantable::write.tab(res,file= paste("AFC_",Ucond[1],"_", Ucond[2],".tsv",sep=""))




results <- data.frame(log2FoldChange =  tvals$fchange, pvalue= tvals$pvaladj, labels=rownames(tdatalog2) )
results$isPValue <-  tvals$pvaladj <0.05
pthresh <- 0.05
log2FCThresh <- 1

#write.tab(paste(results$labels,"_HUMAN",sep="" ), file="string/AllProteins.txt")

p <-ggplot(results, aes(log2FoldChange, -log10(pvalue))) + geom_point(mapping=aes(x=log2FoldChange, y=-log10(pvalue)), size=2)

p <- p + ggplot2::geom_hline(yintercept=-log10(pthresh), col=4, lty=2) 
p <- p + ggplot2::geom_vline(xintercept=c(-log2FCThresh,log2FCThresh), col=4,lty=2) 
p <- p + ggplot2::labs(x = expression(log[2](healthy/diseased)))

filtres <- subset(results, (pvalue<pthresh & abs(log2FoldChange)>log2FCThresh) )

filtreX <- subset(results,  (pvalue<pthresh & abs(log2FoldChange)>log2FCThresh) )
trash <- data.frame(paste(filtreX$labels,"_HUMAN",sep="" ), color = "#00ff00")

#quantable::write.tab(trash, file="string/Regulated.txt")

p = p + geom_text_repel(data=filtres, aes_string(label='labels'))#, size=size, segment.size = segment.size, segment.alpha = segement.alpha)
print(p)

library(pROC)
library(plyr)
head(data2Conditions)

lDat <- dlply(data2Conditions, .(Protein))
lROC <- dlply(data2Conditions, .(Protein) , function(x){roc <- pROC::roc(Condition ~ Intensity,x); roc})

AUC <- ldply(lROC, function(x){c("AUC"= pROC::auc(x))})

topAUC <- plyr::arrange(AUC, AUC , decreasing=TRUE)[1:12,]

#quantable::write.tab(AUC,file= paste("AUC_",Ucond[1],"_", Ucond[2],".tsv",sep=""))

lROCTOP <- lROC[c(as.character(topAUC$Protein))]
lDatTop <- lDat[c(as.character(topAUC$Protein))]

par(mfrow=c(4,3))
for(i in 1:length(lROCTOP)){
  plot(lROCTOP[[i]],main=names(lROCTOP)[i])
  plot(smooth(lROCTOP[[i]]), add=T ,col="gray")
  legend("bottomright", legend=paste("AUC = ",round(pROC::auc(lROCTOP[[i]]),digits=2)), bty="n")
}

lDatTopAll <- rbind.fill(lDatTop)
ggplot(lDatTopAll, aes(x = Condition, y = Intensity)) +
        geom_boxplot() + facet_wrap(~ Protein) + labs(y=expression(log[2](L/H))) + theme_light()

par(mfrow=c(4,3))
for(i in 1:length(lDatTop)){
  boxplot(Intensity ~ Condition, lDatTop[[i]],main=names(lDatTop)[i], ylab=expression(log[2](L/H)))
  stripchart(Intensity ~ Condition, lDatTop[[i]], add=T, vertical = TRUE, method = "jitter",col = "maroon", bg = "bisque")
}