R/plotMutations.R
In MD-Anderson-Bioinformatics/GeneSurvey: MD Anderson Gene Survey
Defines functions
loadGeneMutationDetails
rowLabelNumbersFromLabels
dividerRowLabels
simplifyRowLabels
makeSilentNonsilent
averageWithin
combineWithin
getPlotSymbol
plotMutations_dna
plotMutations_aminoacid
library(Cairo)
loadGeneMutationDetails <- function(theGene, theZipFile, theVerboseFlag)
{
getMutationDetails_Dataframe(theGene, theZipFile, theVerboseFlag)
}
rowLabelNumbersFromLabels <- function(theRowLabels)
{
currentIndex <- 0
matchedLabels <- c()
rowNumbers <- c()
for (label in theRowLabels)
{
if (label %in% matchedLabels)
{
# use currentIndex
rowNumbers <- c(rowNumbers, currentIndex)
}
else
{
# increment currentIndex
currentIndex <- currentIndex + 1
# add to matchedLabels
matchedLabels <- c(matchedLabels, label)
# add row number with updated currentIndex
rowNumbers <- c(rowNumbers, currentIndex)
}
}
rowNumbers
}
dividerRowLabels <- function(theRowLabels)
{
theRowLabels <- as.vector(unlist(lapply(theRowLabels, function(theVal)
{
strsplit(theVal, "-", fixed=TRUE)[[1]][1]
})))
newRowLabels <- c()
for(rowLabel in theRowLabels)
{
if (rowLabel %in% newRowLabels)
{
newRowLabels <- c(newRowLabels, "")
}
else
{
newRowLabels <- c(newRowLabels, rowLabel)
}
}
newRowLabels
}
simplifyRowLabels <- function(theRowLabels, theRowNumbers)
{
theRowLabels <- as.vector(unlist(lapply(theRowLabels, function(theVal)
{
strsplit(theVal, "-", fixed=TRUE)[[1]][1]
})))
combinedLabels <- c()
for(index in 1:length(theRowNumbers))
{
combinedLabels[theRowNumbers[index]] <- theRowLabels[index]
}
theRowLabels <- combinedLabels
newRowLabels <- c()
firstIndex <- 0
indexedLabel <- ""
for(index in 1:length(theRowLabels))
{
rowLabel <- theRowLabels[index]
newRowLabels <- c(newRowLabels, "")
if (indexedLabel!=rowLabel)
{
# first take care of old label
if (0!=firstIndex)
{
newRowLabels[floor((firstIndex+index)/2)] <- indexedLabel
}
# then setup for new label
indexedLabel <- rowLabel
firstIndex <- index
}
}
newRowLabels[floor((firstIndex+length(theRowLabels))/2)] <- indexedLabel
newRowLabels
}
makeSilentNonsilent <- function(theTypes)
{
theTypes[which(theTypes!="Silent")] <- "Nonsilent"
theTypes
}
averageWithin <- function(theValues, theClosest)
{
newVector <- c(theValues[1])
for(nextIndex in 2:length(theValues))
{
testValue <- theValues[nextIndex]
check <- abs(newVector[length(newVector)]-testValue)
if (check>=theClosest)
{
newVector <- c(newVector, testValue)
}
}
newVector
}
combineWithin <- function(theValues, theClosest)
{
newVector <- c(theValues[1])
for(nextIndex in 2:length(theValues))
{
testValue <- theValues[nextIndex]
check <- abs(newVector[length(newVector)]-testValue)
if (check<=theClosest)
{
testValue <- newVector[length(newVector)]
}
newVector <- c(newVector, testValue)
}
newVector
}
# ******************************************************************
# ******************************************************************
# ******************************************************************
# ******************************************************************
getPlotSymbol <- function(thePlotCount)
{
plotSymbol <- 1
if ((thePlotCount>0)&&(thePlotCount<=2))
{
plotSymbol <- 1
}
if (thePlotCount>2)
{
plotSymbol <- 16
}
plotSymbol
}
plotMutations_dna <- function(theGene, theOutputDirectory, theZipFile="/geneSurveyData/GeneSurvey.zip", theVerboseFlag=FALSE)
{
sortColumn1 <- "Disease_Type"
sortColumn2 <- "Variant_Classification"
geneData <- getMetadata_Gene_Mutations(theGene, theZipFile, theVerboseFlag)[[1]][[1]]
plotFile <- c()
if(!is.null(geneData))
{
geneStart <- get.LocationStart(geneData)
geneEnd <- get.LocationEnd(geneData)
mutationTypeStandards <-c("Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", "In_Frame_Ins", "Intron", "Missense_Mutation", "Nonsense_Mutation", "RNA", "Silent", "Splice_Site");
colorSelection <- c("red", "darkgoldenrod", "darkred", "darkorange", "blue", "magenta", "plum", "purple", "green", "darkgreen")
names(colorSelection) <- mutationTypeStandards
#sortColumn <- "Position_Start"
#sortColumn <- "Disease_Type"
plotTypeColumn <- "Variant_Classification"
startLocationColumn <- "Position_Start"
endLocationColumn <- "Position_End"
labelColumn <- "Tumor_Sample_Barcode"
geneColumn <- "Gene"
diseaseColumn <- "Disease_Type"
annotations <- loadGeneMutationDetails(theGene, theZipFile, theVerboseFlag)
annotations <- annotations[order(annotations[sortColumn2]),]
annotations <- annotations[annotations$Position_Start>=geneStart,]
annotations <- annotations[annotations$Position_End<=geneEnd,]
annotations <- annotations[order(annotations[sortColumn1], decreasing=TRUE),]
plotFile <- file.path(theOutputDirectory, paste("Mutations_DNA_", theGene, "_", sortColumn1, "-", sortColumn2, ".PNG", sep=""))
## TODO: Do I need to take into account mixed plus and minus strands?
labels <- as.vector(unlist(annotations[labelColumn]))
starts <- as.numeric(as.vector(unlist(annotations[startLocationColumn])))
#message("plotMutations_dna starts=", paste(starts, sep = ",", collapse = ","))
types <- as.vector(unlist(annotations[plotTypeColumn]))
diseases <- toupper(as.vector(unlist(annotations[diseaseColumn])))
title <- paste("Gene Mutations", theGene, "width =", abs(geneStart - geneEnd), "N=", sum(!is.na(starts)))
rowNumbers <- c(1:length(labels))
rowLabels <- paste(diseases, types, sep="-")
rowLabelNumbers <- rowLabelNumbersFromLabels(rowLabels)
rowLabelsSimplified <- simplifyRowLabels(rowLabels, rowLabelNumbers)
rowLabelDividers <- dividerRowLabels(rowLabels)
#
plotDiseases <- unique(sort(diseases))
plotTypes <- unique(sort(as.vector(unlist(annotations[plotTypeColumn]))))
myWidth <- (12*length(unique(sort(rowLabels))))
#myHeight <- (12*length(unique(sort(rowLabels))))
myHeight <- (24*length(unique(sort(rowLabels))))
if (myWidth < 1000)
{
myWidth <- 1000
}
if (myHeight < 1000)
{
myHeight <- 1000
}
#CairoPNG(filename=plotFile, width=1000, height=)
verboseMessage("plotMutations_dna plotFile=", plotFile)
CairoPNG(filename=plotFile, width=myWidth, height=myHeight)
on.exit(dev.off(), add = TRUE)
#plot.new()
op <- par(no.readonly = TRUE)
on.exit(par(op), add = TRUE)
# c(bottom, left, top, right)
#par(mar=c(17,17,5,5))
# c(11,8,5,5)
####par(xpd=TRUE, mar=c(12,11,5,15))
par(xpd=TRUE, mar=c(0,11,5,15))
# the par family does not work with Cairo
par(family="mono")
##############################################################################
##############################################################################
# mgp=c(6, 1, 0)
par(fig=c(0,1,.3,1), new=TRUE)
plot(1, type="n", las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
xlab=startLocationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2), mgp=c(10, 1, 0), main=title)
##plot(x=starts, y=rowLabelNumbers, col=colorList, las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
## xlab=startLocationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2), mgp=c(6, 1, 0), main=title)
#xlab=startLocationColumn, ylab=labelColumn, mgp=c(15, 1, 0), main=title)
for(myDisease in plotDiseases)
{
startsSelected <- starts[which(diseases==myDisease)]
typesSelected <- types[which(diseases==myDisease)]
rowsSelected <- rowLabelNumbers[which(diseases==myDisease)]
typeIndex <- rowsSelected
names(typeIndex) <- typesSelected
typeIndex <- typeIndex[!duplicated(typeIndex)]
myTable <- table(typesSelected, startsSelected)
for(myType in names(typeIndex))
{
for(myStart in colnames(myTable))
{
myPlotCount <- as.numeric(myTable[myType, myStart])
if (myPlotCount>0)
{
myRow <- as.vector(unlist(typeIndex[myType]))
myColor <- as.vector(unlist(colorSelection[myType]))
points(x=myStart, y=myRow, col=myColor, pch=getPlotSymbol(myPlotCount))
}
}
}
}
verboseMessage("lines")
for(index in 2:length(rowLabelNumbers))
{
if(""!=rowLabelDividers[index])
{
myRowNum <- rowLabelNumbers[index]-0.5
#print(myRowNum)
lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
}
}
#### myRowNum <- rowLabelNumbers[length(rowLabelNumbers)]+0.5
#### lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
#
axis(2, at=1:length(rowLabelsSimplified), labels=rowLabelsSimplified, las=2, tick=FALSE)
# width of diagram is myWidth
# 20 is a magic number based on general height of text
divisor <- 100*(abs(geneStart - geneEnd)/myWidth)
xAxisLabels <- averageWithin(c(geneStart, sort(starts), geneEnd), divisor)
if (geneStart!=xAxisLabels[1])
{
xAxisLabels[1] <- geneStart
}
if (geneEnd!=xAxisLabels[length(xAxisLabels)])
{
xAxisLabels[length(xAxisLabels)] <- geneEnd
}
#axis(1, at=c(geneStart, geneEnd), labels=c(geneStart, geneEnd), las=2)
#message("plotMutations_dna xAxisLabels=", paste(xAxisLabels, sep = ",", collapse = ","))
#message("plotMutations_dna geneStart=", geneStart)
#message("plotMutations_dna geneEnd=", geneEnd)
#axis(1, at=xAxisLabels, labels=xAxisLabels, las=2, cex.axis=2)
legend(geneEnd+divisor, median(rowLabelNumbers), legend=mutationTypeStandards, fill=colorSelection, title="Mutation Types")
legend(geneEnd+divisor, max(rowLabelNumbers), legend=c("1-2 Mutations", ">=3 Mutations"), pch=c(1, 16), title="Mutation Counts")
##############################################################################
##############################################################################
par(fig=c(0,1,0,.3), new=TRUE)
#par(xpd=TRUE, mar=c(12,11,5,15))
## par(xpd=TRUE, mar=c(12,11,0.05,15))
par(xpd=TRUE, mar=c(12,12.5,0.05,16.5))
plotGeneArchitecture(theGene, geneStart, geneEnd, xAxisLabels, divisor, theZipFile, theVerboseFlag)
##############################################################################
##############################################################################
}
plotFile
}
# ******************************************************************
# ******************************************************************
# ******************************************************************
# ******************************************************************
plotMutations_aminoacid <- function(theGene, theOutputDirectory, theZipFile="/geneSurveyData/GeneSurvey.zip", theVerboseFlag=FALSE)
{
sortColumn1 <- "Disease_Type"
sortColumn2 <- "Variant_Classification"
# no protein size data available
#geneData <- getMetadata_Gene_Mutations(theGene, theZipFile, theVerboseFlag)
#geneStart <- get.LocationStart(geneData)
#geneEnd <- get.LocationEnd(geneData)
mutationTypeStandards <-c("Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", "In_Frame_Ins", "Intron", "Missense_Mutation", "Nonsense_Mutation", "RNA", "Silent", "Splice_Site");
colorSelection <- c("red", "darkgoldenrod", "darkred", "darkorange", "blue", "magenta", "plum", "purple", "green", "darkgreen")
names(colorSelection) <- mutationTypeStandards
plotTypeColumn <- "Variant_Classification"
locationColumn <- "amino_acid_position"
labelColumn <- "Tumor_Sample_Barcode"
geneColumn <- "Gene"
diseaseColumn <- "Disease_Type"
annotations <- loadGeneMutationDetails(theGene, theZipFile, theVerboseFlag)
annotations <- annotations[order(annotations[sortColumn2]),]
annotations <- annotations[order(annotations[sortColumn1], decreasing=TRUE),]
plotFile <- file.path(theOutputDirectory, paste("Mutations_AminoAcid_", theGene, "_", sortColumn1, "-", sortColumn2, ".PNG", sep=""))
## TODO: Do I need to take into account mixed plus and minus strands?
starts <- as.vector(unlist(annotations[locationColumn]))
starts <- as.numeric(starts)
geneStart <- min(starts, na.rm = TRUE)
geneEnd <- max(starts, na.rm = TRUE)
labels <- as.vector(unlist(annotations[labelColumn]))
title <- paste("Amino Acid Mutations", theGene, "width =", abs(geneStart - geneEnd), "N=", sum(!is.na(starts)))
types <- as.vector(unlist(annotations[plotTypeColumn]))
diseases <- toupper(as.vector(unlist(annotations[diseaseColumn])))
rowNumbers <- c(1:length(labels))
rowLabels <- paste(diseases, types, sep="-")
rowLabelNumbers <- rowLabelNumbersFromLabels(rowLabels)
rowLabelsSimplified <- simplifyRowLabels(rowLabels, rowLabelNumbers)
rowLabelDividers <- dividerRowLabels(rowLabels)
#
plotDiseases <- unique(sort(diseases))
plotTypes <- unique(sort(as.vector(unlist(annotations[plotTypeColumn]))))
myWidth <- (12*length(unique(sort(rowLabels))))
myHeight <- (12*length(unique(sort(rowLabels))))
if (myWidth < 1000)
{
myWidth <- 1000
}
if (myHeight < 1000)
{
myHeight <- 1000
}
#CairoPNG(filename=plotFile, width=1000, height=)
verboseMessage("plotMutations_aminoacid plotFile=", plotFile)
CairoPNG(filename=plotFile, width=myWidth, height=myHeight)
on.exit(dev.off(), add = TRUE)
#plot.new()
op <- par(no.readonly = TRUE)
on.exit(par(op), add = TRUE)
# c(bottom, left, top, right)
#par(mar=c(17,17,5,5))
# c(11,8,5,5)
par(xpd=TRUE, mar=c(10,9,5,15))
# the par family does not work with Cairo
par(family="mono")
#print("geneStart")
#print(geneStart)
#print("geneEnd")
#print(geneEnd)
# mgp=c(6, 1, 0) axis title, axis labels and axis line
# mar=c(5, 4, 4, 2) + 0.1 c(bottom, left, top, right)
plot(1, type="n", las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
xlab=locationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2),
mgp=c(8, 1, 0), main=title)
##plot(x=starts, y=rowLabelNumbers, col=colorList, las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
## xlab=startLocationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2), mgp=c(6, 1, 0), main=title)
#xlab=startLocationColumn, ylab=labelColumn, mgp=c(15, 1, 0), main=title)
for(myDisease in plotDiseases)
{
startsSelected <- starts[which(diseases==myDisease)]
typesSelected <- types[which(diseases==myDisease)]
rowsSelected <- rowLabelNumbers[which(diseases==myDisease)]
typeIndex <- rowsSelected
names(typeIndex) <- typesSelected
typeIndex <- typeIndex[!duplicated(typeIndex)]
myTable <- table(typesSelected, startsSelected)
for(myType in names(typeIndex))
{
for(myStart in colnames(myTable))
{
myPlotCount <- as.numeric(myTable[myType, myStart])
if (myPlotCount>0)
{
myRow <- as.vector(unlist(typeIndex[myType]))
myColor <- as.vector(unlist(colorSelection[myType]))
points(x=myStart, y=myRow, col=myColor, pch=getPlotSymbol(myPlotCount))
}
}
}
}
for(index in 2:length(rowLabelNumbers))
{
if(""!=rowLabelDividers[index])
{
myRowNum <- rowLabelNumbers[index]-0.5
lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
}
}
#### myRowNum <- rowLabelNumbers[length(rowLabelNumbers)]+0.5
#### lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
#
axis(2, at=1:length(rowLabelsSimplified), labels=rowLabelsSimplified, las=2, tick=FALSE)
# width of diagram is myWidth
divisor <- 100*(abs(geneStart - geneEnd)/myWidth)
xAxisLabels <- averageWithin(c(geneStart, sort(starts), geneEnd), divisor)
#print("xAxisLabels1")
#print(xAxisLabels)
if (geneStart!=xAxisLabels[1])
{
xAxisLabels[1] <- geneStart
}
#print("xAxisLabels2")
#print(xAxisLabels)
if (geneEnd!=xAxisLabels[length(xAxisLabels)])
{
xAxisLabels[length(xAxisLabels)] <- geneEnd
}
#print("xAxisLabels3")
#print(xAxisLabels)
axis(1, at=xAxisLabels, labels=xAxisLabels, las=2, cex.axis=2)
legend(geneEnd+divisor, median(rowLabelNumbers), legend=mutationTypeStandards, fill=colorSelection, title="Mutation Types")
legend(geneEnd+divisor, max(rowLabelNumbers), legend=c("1-2 Mutations", ">=3 Mutations"), pch=c(1, 16), title="Mutation Counts")
plotFile
}
# ******************************************************************
# ******************************************************************
# ******************************************************************
# ******************************************************************
MD-Anderson-Bioinformatics/GeneSurvey documentation built on May 7, 2019, 2:04 p.m.
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Defines functions loadGeneMutationDetails rowLabelNumbersFromLabels dividerRowLabels simplifyRowLabels makeSilentNonsilent averageWithin combineWithin getPlotSymbol plotMutations_dna plotMutations_aminoacid
library(Cairo)
loadGeneMutationDetails <- function(theGene, theZipFile, theVerboseFlag)
{
getMutationDetails_Dataframe(theGene, theZipFile, theVerboseFlag)
}
rowLabelNumbersFromLabels <- function(theRowLabels)
{
currentIndex <- 0
matchedLabels <- c()
rowNumbers <- c()
for (label in theRowLabels)
{
if (label %in% matchedLabels)
{
# use currentIndex
rowNumbers <- c(rowNumbers, currentIndex)
}
else
{
# increment currentIndex
currentIndex <- currentIndex + 1
# add to matchedLabels
matchedLabels <- c(matchedLabels, label)
# add row number with updated currentIndex
rowNumbers <- c(rowNumbers, currentIndex)
}
}
rowNumbers
}
dividerRowLabels <- function(theRowLabels)
{
theRowLabels <- as.vector(unlist(lapply(theRowLabels, function(theVal)
{
strsplit(theVal, "-", fixed=TRUE)[[1]][1]
})))
newRowLabels <- c()
for(rowLabel in theRowLabels)
{
if (rowLabel %in% newRowLabels)
{
newRowLabels <- c(newRowLabels, "")
}
else
{
newRowLabels <- c(newRowLabels, rowLabel)
}
}
newRowLabels
}
simplifyRowLabels <- function(theRowLabels, theRowNumbers)
{
theRowLabels <- as.vector(unlist(lapply(theRowLabels, function(theVal)
{
strsplit(theVal, "-", fixed=TRUE)[[1]][1]
})))
combinedLabels <- c()
for(index in 1:length(theRowNumbers))
{
combinedLabels[theRowNumbers[index]] <- theRowLabels[index]
}
theRowLabels <- combinedLabels
newRowLabels <- c()
firstIndex <- 0
indexedLabel <- ""
for(index in 1:length(theRowLabels))
{
rowLabel <- theRowLabels[index]
newRowLabels <- c(newRowLabels, "")
if (indexedLabel!=rowLabel)
{
# first take care of old label
if (0!=firstIndex)
{
newRowLabels[floor((firstIndex+index)/2)] <- indexedLabel
}
# then setup for new label
indexedLabel <- rowLabel
firstIndex <- index
}
}
newRowLabels[floor((firstIndex+length(theRowLabels))/2)] <- indexedLabel
newRowLabels
}
makeSilentNonsilent <- function(theTypes)
{
theTypes[which(theTypes!="Silent")] <- "Nonsilent"
theTypes
}
averageWithin <- function(theValues, theClosest)
{
newVector <- c(theValues[1])
for(nextIndex in 2:length(theValues))
{
testValue <- theValues[nextIndex]
check <- abs(newVector[length(newVector)]-testValue)
if (check>=theClosest)
{
newVector <- c(newVector, testValue)
}
}
newVector
}
combineWithin <- function(theValues, theClosest)
{
newVector <- c(theValues[1])
for(nextIndex in 2:length(theValues))
{
testValue <- theValues[nextIndex]
check <- abs(newVector[length(newVector)]-testValue)
if (check<=theClosest)
{
testValue <- newVector[length(newVector)]
}
newVector <- c(newVector, testValue)
}
newVector
}
# ******************************************************************
# ******************************************************************
# ******************************************************************
# ******************************************************************
getPlotSymbol <- function(thePlotCount)
{
plotSymbol <- 1
if ((thePlotCount>0)&&(thePlotCount<=2))
{
plotSymbol <- 1
}
if (thePlotCount>2)
{
plotSymbol <- 16
}
plotSymbol
}
plotMutations_dna <- function(theGene, theOutputDirectory, theZipFile="/geneSurveyData/GeneSurvey.zip", theVerboseFlag=FALSE)
{
sortColumn1 <- "Disease_Type"
sortColumn2 <- "Variant_Classification"
geneData <- getMetadata_Gene_Mutations(theGene, theZipFile, theVerboseFlag)[[1]][[1]]
plotFile <- c()
if(!is.null(geneData))
{
geneStart <- get.LocationStart(geneData)
geneEnd <- get.LocationEnd(geneData)
mutationTypeStandards <-c("Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", "In_Frame_Ins", "Intron", "Missense_Mutation", "Nonsense_Mutation", "RNA", "Silent", "Splice_Site");
colorSelection <- c("red", "darkgoldenrod", "darkred", "darkorange", "blue", "magenta", "plum", "purple", "green", "darkgreen")
names(colorSelection) <- mutationTypeStandards
#sortColumn <- "Position_Start"
#sortColumn <- "Disease_Type"
plotTypeColumn <- "Variant_Classification"
startLocationColumn <- "Position_Start"
endLocationColumn <- "Position_End"
labelColumn <- "Tumor_Sample_Barcode"
geneColumn <- "Gene"
diseaseColumn <- "Disease_Type"
annotations <- loadGeneMutationDetails(theGene, theZipFile, theVerboseFlag)
annotations <- annotations[order(annotations[sortColumn2]),]
annotations <- annotations[annotations$Position_Start>=geneStart,]
annotations <- annotations[annotations$Position_End<=geneEnd,]
annotations <- annotations[order(annotations[sortColumn1], decreasing=TRUE),]
plotFile <- file.path(theOutputDirectory, paste("Mutations_DNA_", theGene, "_", sortColumn1, "-", sortColumn2, ".PNG", sep=""))
## TODO: Do I need to take into account mixed plus and minus strands?
labels <- as.vector(unlist(annotations[labelColumn]))
starts <- as.numeric(as.vector(unlist(annotations[startLocationColumn])))
#message("plotMutations_dna starts=", paste(starts, sep = ",", collapse = ","))
types <- as.vector(unlist(annotations[plotTypeColumn]))
diseases <- toupper(as.vector(unlist(annotations[diseaseColumn])))
title <- paste("Gene Mutations", theGene, "width =", abs(geneStart - geneEnd), "N=", sum(!is.na(starts)))
rowNumbers <- c(1:length(labels))
rowLabels <- paste(diseases, types, sep="-")
rowLabelNumbers <- rowLabelNumbersFromLabels(rowLabels)
rowLabelsSimplified <- simplifyRowLabels(rowLabels, rowLabelNumbers)
rowLabelDividers <- dividerRowLabels(rowLabels)
#
plotDiseases <- unique(sort(diseases))
plotTypes <- unique(sort(as.vector(unlist(annotations[plotTypeColumn]))))
myWidth <- (12*length(unique(sort(rowLabels))))
#myHeight <- (12*length(unique(sort(rowLabels))))
myHeight <- (24*length(unique(sort(rowLabels))))
if (myWidth < 1000)
{
myWidth <- 1000
}
if (myHeight < 1000)
{
myHeight <- 1000
}
#CairoPNG(filename=plotFile, width=1000, height=)
verboseMessage("plotMutations_dna plotFile=", plotFile)
CairoPNG(filename=plotFile, width=myWidth, height=myHeight)
on.exit(dev.off(), add = TRUE)
#plot.new()
op <- par(no.readonly = TRUE)
on.exit(par(op), add = TRUE)
# c(bottom, left, top, right)
#par(mar=c(17,17,5,5))
# c(11,8,5,5)
####par(xpd=TRUE, mar=c(12,11,5,15))
par(xpd=TRUE, mar=c(0,11,5,15))
# the par family does not work with Cairo
par(family="mono")
##############################################################################
##############################################################################
# mgp=c(6, 1, 0)
par(fig=c(0,1,.3,1), new=TRUE)
plot(1, type="n", las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
xlab=startLocationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2), mgp=c(10, 1, 0), main=title)
##plot(x=starts, y=rowLabelNumbers, col=colorList, las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
## xlab=startLocationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2), mgp=c(6, 1, 0), main=title)
#xlab=startLocationColumn, ylab=labelColumn, mgp=c(15, 1, 0), main=title)
for(myDisease in plotDiseases)
{
startsSelected <- starts[which(diseases==myDisease)]
typesSelected <- types[which(diseases==myDisease)]
rowsSelected <- rowLabelNumbers[which(diseases==myDisease)]
typeIndex <- rowsSelected
names(typeIndex) <- typesSelected
typeIndex <- typeIndex[!duplicated(typeIndex)]
myTable <- table(typesSelected, startsSelected)
for(myType in names(typeIndex))
{
for(myStart in colnames(myTable))
{
myPlotCount <- as.numeric(myTable[myType, myStart])
if (myPlotCount>0)
{
myRow <- as.vector(unlist(typeIndex[myType]))
myColor <- as.vector(unlist(colorSelection[myType]))
points(x=myStart, y=myRow, col=myColor, pch=getPlotSymbol(myPlotCount))
}
}
}
}
verboseMessage("lines")
for(index in 2:length(rowLabelNumbers))
{
if(""!=rowLabelDividers[index])
{
myRowNum <- rowLabelNumbers[index]-0.5
#print(myRowNum)
lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
}
}
#### myRowNum <- rowLabelNumbers[length(rowLabelNumbers)]+0.5
#### lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
#
axis(2, at=1:length(rowLabelsSimplified), labels=rowLabelsSimplified, las=2, tick=FALSE)
# width of diagram is myWidth
# 20 is a magic number based on general height of text
divisor <- 100*(abs(geneStart - geneEnd)/myWidth)
xAxisLabels <- averageWithin(c(geneStart, sort(starts), geneEnd), divisor)
if (geneStart!=xAxisLabels[1])
{
xAxisLabels[1] <- geneStart
}
if (geneEnd!=xAxisLabels[length(xAxisLabels)])
{
xAxisLabels[length(xAxisLabels)] <- geneEnd
}
#axis(1, at=c(geneStart, geneEnd), labels=c(geneStart, geneEnd), las=2)
#message("plotMutations_dna xAxisLabels=", paste(xAxisLabels, sep = ",", collapse = ","))
#message("plotMutations_dna geneStart=", geneStart)
#message("plotMutations_dna geneEnd=", geneEnd)
#axis(1, at=xAxisLabels, labels=xAxisLabels, las=2, cex.axis=2)
legend(geneEnd+divisor, median(rowLabelNumbers), legend=mutationTypeStandards, fill=colorSelection, title="Mutation Types")
legend(geneEnd+divisor, max(rowLabelNumbers), legend=c("1-2 Mutations", ">=3 Mutations"), pch=c(1, 16), title="Mutation Counts")
##############################################################################
##############################################################################
par(fig=c(0,1,0,.3), new=TRUE)
#par(xpd=TRUE, mar=c(12,11,5,15))
## par(xpd=TRUE, mar=c(12,11,0.05,15))
par(xpd=TRUE, mar=c(12,12.5,0.05,16.5))
plotGeneArchitecture(theGene, geneStart, geneEnd, xAxisLabels, divisor, theZipFile, theVerboseFlag)
##############################################################################
##############################################################################
}
plotFile
}
# ******************************************************************
# ******************************************************************
# ******************************************************************
# ******************************************************************
plotMutations_aminoacid <- function(theGene, theOutputDirectory, theZipFile="/geneSurveyData/GeneSurvey.zip", theVerboseFlag=FALSE)
{
sortColumn1 <- "Disease_Type"
sortColumn2 <- "Variant_Classification"
# no protein size data available
#geneData <- getMetadata_Gene_Mutations(theGene, theZipFile, theVerboseFlag)
#geneStart <- get.LocationStart(geneData)
#geneEnd <- get.LocationEnd(geneData)
mutationTypeStandards <-c("Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", "In_Frame_Ins", "Intron", "Missense_Mutation", "Nonsense_Mutation", "RNA", "Silent", "Splice_Site");
colorSelection <- c("red", "darkgoldenrod", "darkred", "darkorange", "blue", "magenta", "plum", "purple", "green", "darkgreen")
names(colorSelection) <- mutationTypeStandards
plotTypeColumn <- "Variant_Classification"
locationColumn <- "amino_acid_position"
labelColumn <- "Tumor_Sample_Barcode"
geneColumn <- "Gene"
diseaseColumn <- "Disease_Type"
annotations <- loadGeneMutationDetails(theGene, theZipFile, theVerboseFlag)
annotations <- annotations[order(annotations[sortColumn2]),]
annotations <- annotations[order(annotations[sortColumn1], decreasing=TRUE),]
plotFile <- file.path(theOutputDirectory, paste("Mutations_AminoAcid_", theGene, "_", sortColumn1, "-", sortColumn2, ".PNG", sep=""))
## TODO: Do I need to take into account mixed plus and minus strands?
starts <- as.vector(unlist(annotations[locationColumn]))
starts <- as.numeric(starts)
geneStart <- min(starts, na.rm = TRUE)
geneEnd <- max(starts, na.rm = TRUE)
labels <- as.vector(unlist(annotations[labelColumn]))
title <- paste("Amino Acid Mutations", theGene, "width =", abs(geneStart - geneEnd), "N=", sum(!is.na(starts)))
types <- as.vector(unlist(annotations[plotTypeColumn]))
diseases <- toupper(as.vector(unlist(annotations[diseaseColumn])))
rowNumbers <- c(1:length(labels))
rowLabels <- paste(diseases, types, sep="-")
rowLabelNumbers <- rowLabelNumbersFromLabels(rowLabels)
rowLabelsSimplified <- simplifyRowLabels(rowLabels, rowLabelNumbers)
rowLabelDividers <- dividerRowLabels(rowLabels)
#
plotDiseases <- unique(sort(diseases))
plotTypes <- unique(sort(as.vector(unlist(annotations[plotTypeColumn]))))
myWidth <- (12*length(unique(sort(rowLabels))))
myHeight <- (12*length(unique(sort(rowLabels))))
if (myWidth < 1000)
{
myWidth <- 1000
}
if (myHeight < 1000)
{
myHeight <- 1000
}
#CairoPNG(filename=plotFile, width=1000, height=)
verboseMessage("plotMutations_aminoacid plotFile=", plotFile)
CairoPNG(filename=plotFile, width=myWidth, height=myHeight)
on.exit(dev.off(), add = TRUE)
#plot.new()
op <- par(no.readonly = TRUE)
on.exit(par(op), add = TRUE)
# c(bottom, left, top, right)
#par(mar=c(17,17,5,5))
# c(11,8,5,5)
par(xpd=TRUE, mar=c(10,9,5,15))
# the par family does not work with Cairo
par(family="mono")
#print("geneStart")
#print(geneStart)
#print("geneEnd")
#print(geneEnd)
# mgp=c(6, 1, 0) axis title, axis labels and axis line
# mar=c(5, 4, 4, 2) + 0.1 c(bottom, left, top, right)
plot(1, type="n", las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
xlab=locationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2),
mgp=c(8, 1, 0), main=title)
##plot(x=starts, y=rowLabelNumbers, col=colorList, las=2, yaxt="n", xaxt="n", xlim=c(geneStart, geneEnd), ylim=c(0, max(rowLabelNumbers)),
## xlab=startLocationColumn, ylab=paste("Samples sorted by", sortColumn1, "and", sortColumn2), mgp=c(6, 1, 0), main=title)
#xlab=startLocationColumn, ylab=labelColumn, mgp=c(15, 1, 0), main=title)
for(myDisease in plotDiseases)
{
startsSelected <- starts[which(diseases==myDisease)]
typesSelected <- types[which(diseases==myDisease)]
rowsSelected <- rowLabelNumbers[which(diseases==myDisease)]
typeIndex <- rowsSelected
names(typeIndex) <- typesSelected
typeIndex <- typeIndex[!duplicated(typeIndex)]
myTable <- table(typesSelected, startsSelected)
for(myType in names(typeIndex))
{
for(myStart in colnames(myTable))
{
myPlotCount <- as.numeric(myTable[myType, myStart])
if (myPlotCount>0)
{
myRow <- as.vector(unlist(typeIndex[myType]))
myColor <- as.vector(unlist(colorSelection[myType]))
points(x=myStart, y=myRow, col=myColor, pch=getPlotSymbol(myPlotCount))
}
}
}
}
for(index in 2:length(rowLabelNumbers))
{
if(""!=rowLabelDividers[index])
{
myRowNum <- rowLabelNumbers[index]-0.5
lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
}
}
#### myRowNum <- rowLabelNumbers[length(rowLabelNumbers)]+0.5
#### lines(x=c(geneStart, geneEnd), y=c(myRowNum, myRowNum), lwd=1)
#
axis(2, at=1:length(rowLabelsSimplified), labels=rowLabelsSimplified, las=2, tick=FALSE)
# width of diagram is myWidth
divisor <- 100*(abs(geneStart - geneEnd)/myWidth)
xAxisLabels <- averageWithin(c(geneStart, sort(starts), geneEnd), divisor)
#print("xAxisLabels1")
#print(xAxisLabels)
if (geneStart!=xAxisLabels[1])
{
xAxisLabels[1] <- geneStart
}
#print("xAxisLabels2")
#print(xAxisLabels)
if (geneEnd!=xAxisLabels[length(xAxisLabels)])
{
xAxisLabels[length(xAxisLabels)] <- geneEnd
}
#print("xAxisLabels3")
#print(xAxisLabels)
axis(1, at=xAxisLabels, labels=xAxisLabels, las=2, cex.axis=2)
legend(geneEnd+divisor, median(rowLabelNumbers), legend=mutationTypeStandards, fill=colorSelection, title="Mutation Types")
legend(geneEnd+divisor, max(rowLabelNumbers), legend=c("1-2 Mutations", ">=3 Mutations"), pch=c(1, 16), title="Mutation Counts")
plotFile
}
# ******************************************************************
# ******************************************************************
# ******************************************************************
# ******************************************************************
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