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ASEcalculations.html
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<h3>ASEcalculations.R</h3>
<p>johanreimegard — <em>Sep 9, 2013, 2:51 PM</em></p>
<pre><code class="r"># TODO: Add comment
#
# Author: johanreimegard
###############################################################################
main <-function(fileName="BWA_genome.raw.all_FREEC50k.repeatRegions.heterozygousRegions.Crubella_183_only_exons_unique.vcf.Sample.vcf.Rfriendly", dataDir="/gulo/proj_nobackup/b2012122/private/ASE",
annotation="BWA_genome.raw.all_FREEC50k.repeatRegions.heterozygousRegions.Crubella_183_only_exons_unique.vcf.Sample.Crubella_183_gene.VCFannotaion",
rounds = 10 ,cutoffNominal=0.005, cutoffAdjusted=0.1){
file <- paste(dataDir,fileName,sep="/")
annotationFile <- paste(dataDir,annotation,sep="/")
#load dataset
print("Reading data file")
sampleData <- read.table(file,header=TRUE,sep ="\t")
print("Reading annotation file")
annotationData <- read.table(annotationFile,header=FALSE,sep ="\t")
q$annotation=annotationData$V3
# read in different samples
DNAInterSamples <- c("Inter3.1","Inter4.1","Inter5.1")
DNAIntraSamples <- c("Intra6.3","Intra7.2","Intra8.2")
RNAInterSamples <- c("Inter3_1_1_F","Inter3_1_1_L","Inter4_1_1_F","Inter4_1_1_L","Inter4_1_2_F","Inter4_1_2_L","Inter4_1_3_F","Inter4_1_4_L","Inter5_1_1_F","Inter5_1_1_L")
RNAIntraSamples <- c("Intra6_3_F","Intra6_3_L","Intra7_2_1_F","Intra7_2_1_L","Intra7_2_2_F","Intra7_2_2_L","Intra7_2_3_F","Intra7_2_3_L","Intra8_2_1_F","Intra8_2_1_L")
AllSamples <- c(DNAInterSamples,DNAIntraSamples,RNAInterSamples,RNAIntraSamples)
#
print("Checking for ASE")
ASEinfo = data.frame()
Inter3_1_DNA <- c("Inter3.1")
Inter3_1_RNA <-c("Inter3_1_1_F","Inter3_1_1_L")
Inter3_1_SampleData <- getPvalues(sampleData,Inter3_1_DNA,Inter3_1_RNA)
print(Inter3_1_SampleData$Inter3.1_Count1,Inter3_1_SampleData$Inter3.1_Count2)
ASEinfo <- rbind(ASEinfo, getASEinfo(Inter3_1_SampleData,Inter3_1_RNA,rounds,cutoffNominal,cutoffAdjusted))
Inter4_1_DNA <- c("Inter4.1")
Inter4_1_RNA <-c("Inter4_1_1_F","Inter4_1_1_L","Inter4_1_2_F","Inter4_1_2_L","Inter4_1_3_F","Inter4_1_4_L")
Inter4_1_RNA_Flower <-c("Inter4_1_1_F","Inter4_1_2_F","Inter4_1_3_F")
Inter4_1_RNA_Leafs <-c("Inter4_1_1_L","Inter4_1_2_L","Inter4_1_4_L")
Inter4_1_SampleDataFlowers <- getPvalues(sampleData,Inter4_1_DNA,Inter4_1_RNA_Flower)
nrOfheterozygousGenesExpressedInIntraFlowers = length(unique(Inter4_1_SampleDataFlowers$annotation))
InterUnionGenesFlowers <- getASEgenesUnion(Inter4_1_SampleDataFlowers,Inter4_1_RNA_Flower,cutoffAdjusted=0.005)
InterIntersectGenesFlowers <- getASEgenesIntersect(Inter4_1_SampleDataFlowers,Inter4_1_RNA_Flower,cutoffAdjusted=0.005)
Inter4_1_SampleDataLeafs <- getPvalues(sampleData,Inter4_1_DNA,Inter4_1_RNA_Leafs)
nrOfheterozygousGenesExpressedInIntraLeafs = length(unique(Inter4_1_SampleDataLeafs$annotation))
InterUnionGenesLeafs <- getASEgenesUnion(Inter4_1_SampleDataLeafs,Inter4_1_RNA_Leafs,cutoffAdjusted=0.005)
InterIntersectGenesLeafs <- getASEgenesIntersect(Inter4_1_SampleDataLeafs,Inter4_1_RNA_Leafs,cutoffAdjusted=0.005)
Both <- intersect(unique(Inter4_1_SampleDataFlowers$annotation),unique(Inter4_1_SampleDataLeafs$annotation))
FlowerUnique <- detDiff(unique(Inter4_1_SampleDataFlowers$annotation),Both)
nrOfheterozygousGenesExpressedInIntra = length(Both)
BothASEUnion = intersect(UnionGenesFlowers,UnionGenesLeafs)
BothASEIntersect = intersect(IntersectGenesFlowers,IntersectGenesLeafs)
Inter4_1_SampleData <- getPvalues(sampleData,Inter4_1_DNA,Inter4_1_RNA)
ASEinfo <- rbind(ASEinfo, getASEinfo(Inter4_1_SampleData,Inter4_1_RNA,rounds,cutoffNominal,cutoffAdjusted))
Inter5_1_DNA <- c("Inter5.1")
Inter5_1_RNA <-c("Inter5_1_1_F","Inter5_1_1_L")
Inter5_1_SampleData <- getPvalues(sampleData,Inter5_1_DNA,Inter5_1_RNA)
ASEinfo <- rbind(ASEinfo, getASEinfo(Inter5_1_SampleData,Inter5_1_RNA,rounds,cutoffNominal,cutoffAdjusted))
Intra6_3_DNA <- c("Intra6.3")
Intra6_3_RNA <-c("Intra6_3_F","Intra6_3_L")
Intra6_3_SampleData <- getPvalues(sampleData,Intra6_3_DNA,Intra6_3_RNA)
ASEinfo <- rbind(ASEinfo, getASEinfo(Intra6_3_SampleData,Intra6_3_RNA,rounds,cutoffNominal,cutoffAdjusted))
Intra7_2_DNA <- c("Intra7.2")
Intra7_2_RNA_Flower <-c("Intra7_2_1_F","Intra7_2_2_F","Intra7_2_3_F")
Intra7_2_RNA_Leafs <-c("Intra7_2_1_L","Intra7_2_2_L","Intra7_2_3_L")
Intra7_2_SampleDataFlower1 <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Flower[1])
Intra7_2_SampleDataFlower2 <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Flower[2])
Intra7_2_SampleDataFlower3 <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Flower[3])
Intra7_2_SampleDataLeafs1 <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Leafs[1])
Intra7_2_SampleDataLeafs2 <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Leafs[2])
Intra7_2_SampleDataLeafs3 <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Leafs[3])
#
Intra7_2_SampleDataFlowers <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Flower)
nrOfheterozygousGenesExpressedInIntraFlowers = length(unique(Intra7_2_SampleDataFlowers$annotation))
IntraUnionGenesFlowers <- getASEgenesUnion(Intra7_2_SampleDataFlowers,Intra7_2_RNA_Flower,cutoffAdjusted=0.005)
IntraIntersectGenesFlowers <- getASEgenesIntersect(Intra7_2_SampleDataFlowers,Intra7_2_RNA_Flower,cutoffAdjusted=0.005)
Intra7_2_SampleDataLeafs <- getPvalues(sampleData,Intra7_2_DNA,Intra7_2_RNA_Leafs)
nrOfheterozygousGenesExpressedInIntraLeafs = length(unique(Intra7_2_SampleDataLeafs$annotation))
IntraUnionGenesLeafs <- getASEgenesUnion(Intra7_2_SampleDataLeafs,Intra7_2_RNA_Leafs,cutoffAdjusted=0.005)
IntraIntersectGenesLeafs <- getASEgenesIntersect(Intra7_2_SampleDataLeafs,Intra7_2_RNA_Leafs,cutoffAdjusted=0.005)
Both <- intersect(unique(Intra7_2_SampleDataFlowers$annotation),unique(Intra7_2_SampleDataLeafs$annotation))
nrOfheterozygousGenesExpressedInIntra = length(Both)
BothASEUnion = intersect(UnionGenesFlowers,UnionGenesLeafs)
BothASEIntersect = intersect(IntersectGenesFlowers,IntersectGenesLeafs)
InterUnionGenesFlowers
InterUnionGenesLeafs
IntraUnionGenesFlowers
IntraUnionGenesLeafs
genes <- unique(sampleData$annotation)
InterFlowersGenes = unique(Inter4_1_SampleDataFlowers$annotation)
InterLeavesGenes = unique(Inter4_1_SampleDataLeafs$annotation)
IntraFlowersGenes = unique(Intra7_2_SampleDataFlowers$annotation)
IntraLeafsGenes = unique(Intra7_2_SampleDataLeafs$annotation)
InterFlowersGenesIndex = match(InterFlowersGenes,genes)
InterLeavesGenesIndex = match(InterLeavesGenes,genes)
IntraFlowersGenesIndex = match(IntraFlowersGenes,genes)
IntraLeafsGenesIndex = match(IntraLeafsGenes,genes)
length(setdiff(InterUnionGenesFlowers,InterUnionGenesLeafs))
length(setdiff(InterUnionGenesLeafs,InterUnionGenesFlowers))
length(union(InterUnionGenesFlowers,InterUnionGenesLeafs))
length(setdiff(IntraUnionGenesFlowers,IntraUnionGenesLeafs))
length(setdiff(IntraUnionGenesLeafs,IntraUnionGenesFlowers))
length(union(IntraUnionGenesFlowers,IntraUnionGenesLeafs))
length(intersect(IntraUnionGenesFlowers,IntraUnionGenesLeafs))
IntraFlowersASE = IntraUnionGenesFlowers
IntraLeafsASE = IntraUnionGenesLeafs
ASEinfo <- rbind(ASEinfo, getASEinfo(Intra7_2_SampleData,Intra7_2_RNA,rounds,cutoffNominal,cutoffAdjusted))
Intra8_2_DNA <- c("Intra8.2")
Intra8_2_RNA <-c("Intra8_2_1_F","Intra8_2_1_L")
Intra8_2_SampleData <- getPvalues(sampleData,Intra8_2_DNA,Intra8_2_RNA)
ASEinfo <- rbind(ASEinfo, getASEinfo(Intra8_2_SampleData,Intra8_2_RNA,rounds,cutoffNominal,cutoffAdjusted))
#Under development
#printPvalues(DataSetInterHeteroAbundantBOTHwithPvalue,RNAInterSamples,DNAInterSamples,"test.pdf")
return (ASEinfo)
}
getPvalues <- function(sampleData,DNAsamples,RNAsamples, RNAlow=40, RNAhigh=2000,DNAlow=30,DNAhigh=200){
# Different filters
# Only keep heterozygous DNAsamples
DataSetFiltered <- filterCallData(sampleData, DNAsamples)
# Only keep heterozygous samples with DNA total count above 30 in all heterozygous samples
DataSetFilteredAbundant <- filterTotalData(DataSetFiltered, DNAsamples,c(DNAlow,DNAhigh))
# Only keep heterozygous samples with DNA total count above 40 in all heterozygous samples
DataSetFilteredAbundantBOTH <- filterTotalData(DataSetFilteredAbundant, RNAsamples,c(RNAlow,RNAhigh))
# Calculate pValues
DataSetFilteredAbundantBOTHwithPvalue <- Pvaluescalculation(DataSetFilteredAbundantBOTH, RNAsamples,DNAsamples)
# Correct for multiple testing
DataSetFilteredAbundantBOTHwithPvalue<-as.data.frame(DataSetFilteredAbundantBOTHwithPvalue)
DataSetInterHeteroAbundantBOTHwithPvalueCorrected <- MultipleTestCorrection(DataSetFilteredAbundantBOTHwithPvalue,RNAsamples)
return(DataSetInterHeteroAbundantBOTHwithPvalueCorrected)
}
printPvalues <- function(Dataset,RNAsamples,DNAsamples, pdfFileName){
pdf(pdfFileName)
par(mfrow=c(length(RNAsamples),2), bty="l", cex=0.6)
for(i in 1:length(RNAsamples)){
for(j in 1:length(DNAsamples[j])){
RNAsample = strsplit(RNAsamples[i], '_')
DNAsample = strsplit(DNAsamples[j], '\\.')
if( RNAsample[[1]][1]==DNAsample[[1]][1]){
name = paste(RNAsamples[i], "pValue", sep="_")
hist(Dataset[name],breaks=40)
name = paste(RNAsamples[i], "fraction", sep="_")
name2 = paste(DNAsamples[j], "fraction", sep="_")
boxScatterPlot(Dataset[name],Dataset[name],ylabText="DNA distribution",xlabText="RNA distribtuion",title = paste( "ASE distribution"))
}
}
}
dev.off()
}
boxScatterPlot <- function(x,y,ylabText="Major readCount",xlabText="Minor readCount",title ="Enhanced Scatterplot"){
par(fig=c(0,0.8,0,0.8), new=TRUE)
plot(x, y , xlab=xlabText,
ylab=ylabText)
par(fig=c(0,0.8,0.55,1), new=TRUE)
boxplot(x, horizontal=TRUE, axes=FALSE)
par(fig=c(0.65,1,0,0.8),new=TRUE)
boxplot(y, axes=FALSE)
mtext(title, side=3, outer=TRUE, line=-3)
}
filterCallData <- function(testData , samples, call="0/1"){
# filter for heterozygous sites in all samples
for(i in 1:length(samples)){
name = paste(samples[i], "Call", sep="_")
testData <- testData[testData[name]==call,]
}
return (testData)
}
filterTotalData <- function(Dataset , samples,cutoff=c(40,200)){
for(i in 1:length(samples)){
name = paste(samples[i], "Total", sep="_")
Dataset <- Dataset[Dataset[name]>cutoff[1] ,]
}
return (Dataset)
}
Pvaluescalculation <- function(testData,RNAsamples,DNAsamples){
for(i in 1:length(RNAsamples)){
for(j in 1:length(DNAsamples)){
RNAsample = strsplit(RNAsamples[i], '_')
DNAsample = strsplit(DNAsamples[j], '\\.')
if( RNAsample[[1]][1]==DNAsample[[1]][1]){
print(paste(DNAsamples[j], RNAsamples[i], sep = " comparing "))
count1RNA=paste(RNAsamples[i], "Count1", sep="_")
TotalRNA=paste(RNAsamples[i], "Total", sep="_")
count1DNA=paste(DNAsamples[j], "Count1", sep="_")
TotalDNA=paste(DNAsamples[j], "Total", sep="_")
pValuesName= paste(RNAsamples[i], "pValue", sep="_")
#print(testData[count1RNA]/testData[TotalRNA])
#print(paste(testData[count1DNA][1], testData[TotalDNA][1], sep = " of total "))
testData[pValuesName]<- apply(testData,1, BinTest, count1RNA, TotalRNA, count1DNA, TotalDNA)
}
}
}
return (testData)
}
MultipleTestCorrection <- function(testData,RNAsamples) {
for(i in 1:length(RNAsamples)){
RNAsample = strsplit(RNAsamples[i], '_')
pValue=paste(RNAsamples[i], "pValue", sep="_")
pValue2= as.numeric(testData[,which(colnames(testData)==pValue)])
pValuesCorrectedName=paste(RNAsamples[i], "pValueCorrected", sep="_")
testData[pValuesCorrectedName]<- p.adjust(pValue2,method="BH")
}
return(testData)
}
BinTest <- function(x, count1RNA, TotalRNA,count1DNA,TotalDNA){
temp <- binom.test(as.numeric(x[count1RNA]),as.numeric(x[TotalRNA]),p=(as.numeric(x[count1DNA])/as.numeric(x[TotalDNA])), alternative="two.sided")
return (temp$p.value)
}
getASEinfo <- function(Dataset,RNAsamples,rounds=10,cutoffNominal=0.005, cutoffAdjusted=0.1){
info = data.frame()
for(i in (1:rounds)){
DatasetOneSNPperGene <- getOneSNPperGene(Dataset)
rowInfo <- getASEinformation(DatasetOneSNPperGene,RNAsamples,cutoffNominal, cutoffAdjusted,i)
info <- rbind(info,rowInfo)
}
return (info)
}
getASEinformation <- function(DatasetOneSNPperGene,RNAsamples,cutoffNominal=0.005, cutoffAdjusted=0.1,round=1){
info = data.frame()
for(i in seq(1,length(RNAsamples)-1)){
columnName <- paste(RNAsamples[i],"pValueCorrected",sep="_")
columnName2 <- paste(RNAsamples[i+1],"pValueCorrected",sep="_")
Flowers <- DatasetOneSNPperGene[which(DatasetOneSNPperGene[columnName] <cutoffAdjusted),]
Leafs <- DatasetOneSNPperGene[which(DatasetOneSNPperGene[columnName2] <cutoffAdjusted),]
LeavesList(RNAsamples[i])=Leafs$annotation
nrOfASEAdjustedFlowers <- length (Flowers[[1]])
nrOfASEAdjustedLeafs <- length (Leafs[[1]])
GeneIntersect <- intersect(Flowers$annotation,Leafs$annotation)
GeneFlower <- setdiff(Flowers$annotation,Leafs$annotation)
GeneLeafs <- setdiff(Leafs$annotation,Flowers$annotation)
nrOfASEAdjustedFlowersAndLeaves <- length (GeneIntersect)
nrOfASEAdjustedFlowersOnly <- length (GeneFlower)
nrOfASEAdjustedLeafsOnly <- length (GeneLeafs)
rowinfo <- data.frame("Name"=RNAsamples[i],"NrOfGenes"=nrOfGenes,"Adjusted_Pvalue"=cutoffAdjusted,"Adjusted_count"=nrOfASEAdjusted)
info <- rbind(info,rowinfo)
}
return (info)
}
getASEgenesUnion <- function(Dataset,RNAsamples,rounds=10,cutoffNominal=0.005, cutoffAdjusted=0.005){
DatasetOneSNPperGene <- getOneSNPperGene(Dataset)
info=NULL
for(i in 1:length(RNAsamples)){
rowInfo <- getASEGenes(DatasetOneSNPperGene,RNAsamples[i],cutoffNominal, cutoffAdjusted,i)
info <- union(info,rowInfo)
}
return (info)
}
getASEgenesIntersect <- function(Dataset,RNAsamples,rounds=10,cutoffNominal=0.005, cutoffAdjusted=0.005){
DatasetOneSNPperGene <- getOneSNPperGene(Dataset)
info=NULL
for(i in 1:length(RNAsamples)){
rowInfo <- getASEGenes(DatasetOneSNPperGene,RNAsamples[i],cutoffNominal, cutoffAdjusted,i)
if(i ==1 ){
info=rowInfo
}else{
info <- intersect(info,rowInfo)
}
}
return (info)
}
getASEGenes <- function(DatasetOneSNPperGene,RNAsample,cutoffNominal=0.005, cutoffAdjusted=0.1,round=1){
columnName <- paste(RNAsample,"pValueCorrected",sep="_")
Flowers <- DatasetOneSNPperGene[which(DatasetOneSNPperGene[columnName] <cutoffAdjusted),]
return(Flowers$annotation)
}
getOneSNPperGene <- function(Dataset,classifier="annotation", cutoff = 0.05){
Dataset$duplicated <- duplicated.random(as.vector(Dataset[,classifier]))
DataSetOneSNPperGene <- subset(Dataset, duplicated == FALSE)
return (DataSetOneSNPperGene)
}
duplicated.random <- function(x, incomparables = FALSE, ...){
if ( is.vector(x) )
{
permutation = sample(length(x))
x.perm = x[permutation]
result.perm = duplicated(x.perm, incomparables, ...)
result = result.perm[order(permutation)]
return(result)
}
else if ( is.matrix(x) )
{
permutation = sample(nrow(x))
x.perm = x[permutation,]
result.perm = duplicated(x.perm, incomparables, ...)
result = result.perm[order(permutation)]
return(result)
}
else
{
stop(paste("duplicated.random() only supports vectors",
"matrices for now."))
}
}
plotVenn <- function(A,B,C,D){
venn.diagram(
x = list(A,B,C,D),
filename = "1D-quadruple_Venn.tiff",
col = "black",
lty = "dotted",
lwd = 4,
fill = c("cornflowerblue", "green", "yellow", "darkorchid1"),
alpha = 0.50,
label.col = c("orange", "white", "darkorchid4", "white", "white", "white", "white", "white", "darkblue", "white", "white", "white", "white", "darkgreen", "white"),
cex = 2.5,
fontfamily = "serif",
fontface = "bold",
cat.col = c("darkblue", "darkgreen", "orange", "darkorchid4"),
cat.cex = 2.5,
cat.fontfamily = "serif"
);
}
</code></pre>
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