### R code from vignette source 'MetaGxBreast.Rnw' ### Encoding: UTF-8 ################################################### ### code chunk number 1: setup (eval = FALSE) ################################################### ## options(keep.source=TRUE, width = 50) ################################################### ### code chunk number 2: install-pkg (eval = FALSE) ################################################### ## if (!requireNamespace("BiocManager", quietly = TRUE)) ## install.packages("BiocManager") ## BiocManager::install("MetaGxBreast") ################################################### ### code chunk number 3: loadlib ################################################### library(MetaGxBreast) esets = MetaGxBreast::loadBreastEsets(loadString = c("CAL", "DFHCC", "DFHCC2", "DFHCC3", "DUKE", "DUKE2", "EMC2"))[[1]] ################################################### ### code chunk number 4: sampleNumber-summary ################################################### numSamples <- vapply(seq_along(esets), FUN=function(i, esets){ length(sampleNames(esets[[i]])) }, numeric(1), esets=esets) SampleNumberSummaryAll <- data.frame(NumberOfSamples = numSamples, row.names = names(esets)) total <- sum(SampleNumberSummaryAll[,"NumberOfSamples"]) SampleNumberSummaryAll <- rbind(SampleNumberSummaryAll, total) rownames(SampleNumberSummaryAll)[nrow(SampleNumberSummaryAll)] <- "Total" require(xtable) print(xtable(SampleNumberSummaryAll,digits = 2), floating = FALSE) ################################################### ### code chunk number 5: sampleNumberSummariesPdata ################################################### #pData Variables pDataID <- c("er","pgr", "her2", "age_at_initial_pathologic_diagnosis", "grade", "dmfs_days", "dmfs_status", "days_to_tumor_recurrence", "recurrence_status", "days_to_death", "vital_status", "sample_type", "treatment") pDataPercentSummaryTable <- NULL pDataSummaryNumbersTable <- NULL pDataSummaryNumbersList = lapply(esets, function(x) vapply(pDataID, function(y) sum(!is.na(pData(x)[,y])), numeric(1))) pDataPercentSummaryList = lapply(esets, function(x) vapply(pDataID, function(y) sum(!is.na(pData(x)[,y]))/nrow(pData(x)), numeric(1))*100) pDataSummaryNumbersTable = sapply(pDataSummaryNumbersList, function(x) x) pDataPercentSummaryTable = sapply(pDataPercentSummaryList, function(x) x) rownames(pDataSummaryNumbersTable) <- pDataID rownames(pDataPercentSummaryTable) <- pDataID colnames(pDataSummaryNumbersTable) <- names(esets) colnames(pDataPercentSummaryTable) <- names(esets) pDataSummaryNumbersTable <- rbind(pDataSummaryNumbersTable, total) rownames(pDataSummaryNumbersTable)[nrow(pDataSummaryNumbersTable)] <- "Total" # Generate a heatmap representation of the pData pDataPercentSummaryTable<-t(pDataPercentSummaryTable) pDataPercentSummaryTable<-cbind(Name=(rownames(pDataPercentSummaryTable)) ,pDataPercentSummaryTable) nba<-pDataPercentSummaryTable gradient_colors = c("#ffffff","#ffffd9","#edf8b1","#c7e9b4","#7fcdbb", "#41b6c4","#1d91c0","#225ea8","#253494","#081d58") library(lattice) nbamat<-as.matrix(nba) rownames(nbamat)<-nbamat[,1] nbamat<-nbamat[,-1] Interval<-as.numeric(c(10,20,30,40,50,60,70,80,90,100)) levelplot(nbamat,col.regions=gradient_colors, main="Available Clinical Annotation", scales=list(x=list(rot=90, cex=0.5), y= list(cex=0.5),key=list(cex=0.2)), at=seq(from=0,to=100,length=10), cex=0.2, ylab="", xlab="", lattice.options=list(), colorkey=list(at=as.numeric(factor(c(seq(from=0, to=100, by=10)))), labels=as.character(c( "0","10%","20%","30%", "40%","50%", "60%", "70%", "80%","90%", "100%"), cex=0.2,font=1,col="brown",height=1, width=1.4), col=(gradient_colors))) ################################################### ### code chunk number 6: sessionInfo ################################################### toLatex(sessionInfo())