inst/doc/MetaGxOvarian.R

In MetaGxOvarian: Transcriptomic Ovarian Cancer Datasets

### R code from vignette source 'MetaGxOvarian.Rnw'
### Encoding: UTF-8

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### code chunk number 1: setup (eval = FALSE)
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## options(keep.source=TRUE, width = 50)


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### code chunk number 2: install-pkg (eval = FALSE)
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## source("http://bioconductor.org/biocLite.R")
## biocLite("MetaGxOvarian")


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### code chunk number 3: loadlib
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library(MetaGxOvarian)
esets = MetaGxOvarian::loadOvarianEsets()[[1]]


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### code chunk number 4: sampleNumber-summary
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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)


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### code chunk number 5: sampleNumberSummariesPdata
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#pData Variables
pDataID <- c("sample_type", "histological_type", "primarysite", "summarygrade",
             "summarystage", "tumorstage", "grade",
             "age_at_initial_pathologic_diagnosis", "pltx", "tax",
             "neo", "days_to_tumor_recurrence", "recurrence_status",
             "days_to_death", "vital_status")


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)))



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### code chunk number 6: sessionInfo
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toLatex(sessionInfo())