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ManhattanPlot.r
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ManhattanPlot.r
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# Copyright (c) 2019 Lars Fritsche
# Manhattan plot Rscript
options(stringsAsFactors=F)
library("optparse")
require("plotrix")
require("data.table")
require("RColorBrewer")
t_white <- grDevices::rgb(t(grDevices::col2rgb("white")), alpha = 100, maxColorValue = 255)
t_black <- grDevices::rgb(t(grDevices::col2rgb("black")), alpha = 75, maxColorValue = 255)
# read very small pvalues and covert to -lop10P values
Ptolog10 <- function(P) {
if (as.numeric(P) > 0) {
log10P <- -log10(as.numeric(P))
} else if (is.na(P) | as.numeric(P) > 1 | as.numeric(P) < 0) {
log10P <- NA
} else {
part1 <- as.numeric(gsub("(.+)[Ee]-.+", "\\1", P))
part1 <- -log10(as.numeric(part1) * 0.1)
part2 <- as.numeric(gsub(".+[Ee]-(.+)", "\\1", P))
part2 <- part2 - 1
log10P <- part1 + part2
}
return(as.numeric(log10P))
}
# see latest version: /net/junglebook/home/larsf/Rfunctions/function.getNearestGene.r
getNearestGene <- function(input,Marker="Marker",chromosome="chromosome",
position="position",build="hg19"){
require(Map2NCBI)
require(data.table)
markers <- input[,c(Marker,chromosome,position),with=F]
names(markers) <- c("Marker","chromosome","position")
markers[chromosome == "X",chromosome:= 23]
file.genelist <- path.expand(paste0("~/ExonList_",build,".txt"))
if(!file.exists(file.genelist)){
files.url <- paste0("http://hgdownload.soe.ucsc.edu/goldenPath/",build,
"/database/ncbiRefSeq",c(".sql",".txt.gz"))
files.temp <- tempfile(fileext=c(".sql",".gz"))
download.file(files.url[2],destfile=files.temp[2])
download.file(files.url[1],destfile=files.temp[1])
header <- readLines(files.temp[1])
header <- header[(grep("^CREATE TABLE",header)+1):(grep("^ KEY",header)[1]-1)]
genetable <- fread(files.temp[2],col.names=gsub(".+`(.+)`.+","\\1",header))
genetable[,chrom:=gsub("^chr","",chrom)]
genetable <- unique(genetable[chrom %in% c(1:22,"X","Y","M") & !grepl("^X",name),
.(name2,chrom,exonStarts,exonEnds)])
exontable <- apply(genetable,1,function(x) {
data.table(
'FeatureName'=x[["name2"]],
'chromosome'=x[["chrom"]],
'start'=as.numeric(strsplit(x[["exonStarts"]],",")[[1]]),
'end'=as.numeric(strsplit(x[["exonEnds"]],",")[[1]]))
})
genetable <- unique(rbindlist(exontable))
genetable <- genetable[order(chromosome,`start`,`end`),]
fwrite(genetable,file.genelist,sep="\t",quote=T)
} else {
genetable <- fread(file.genelist,sep="\t")
}
MappedGenes <- MapMarkers(genetable, markers, nAut=22, other = c("X","Y"),savefiles=F)
MappedGenes <- MappedGenes[,.(Marker,chromosome,position,FeatureName,`Inside?`)]
MappedGenes[chromosome %in% c(23,25),chromosome:="X"]
MappedGenes[chromosome == 24,chromosome:="Y"]
setnames(MappedGenes,c("Marker","chromosome","position","FeatureName","Inside?"),
c(Marker,chromosome,position,"LABEL","RelativeToGene"))
output <- merge(input,MappedGenes,by=c(Marker,chromosome,position))
return(output)
}
# main function to generate Manhattan plots
ManhattanPlot <- function(res,top.size=0.125,break.top=15,hitregion=NULL,
chr="CHROM",pos="POS",pvalue="PVALUE",build="hg19",labelPeaks=T,regionSize=500000,
log10p=F,sigthreshold="5E-8",coltop=F,maintitle="",DTthreads=1) {
# devtools::install_github('JosephCrispell/basicPlotteR')
require(basicPlotteR)
setDTthreads(DTthreads)
if(!is.data.table(res)) res <- as.data.table(res)
setnames(res,c(chr,pos,pvalue),c("CHROM","POS","PVALUE"),skip_absent=T)
# horizontal lines and corresponding colors
yLine <- c(-log10(sort(as.numeric(unlist(strsplit(sigthreshold,","))))))
colLine <- c("red")
if(!log10p) {
res[,LOG10P:=-log10(as.numeric(PVALUE))]
res[as.numeric(PVALUE) == 0,LOG10P:=sapply(PVALUE,Ptolog10)]
} else {
res[,PVALUE:=as.numeric(PVALUE)]
setnames(res,"PVALUE","LOG10P")
}
res <- na.omit(res[!is.infinite(LOG10P),.(CHROM,POS,LOG10P)])
chrs <- c(1:22,"X",23,"Y",24,"XY",25,"MT",26)
chrs <- c(chrs,paste0("chr",chrs))
chrs <- chrs[which(chrs %in% unique(res$CHROM))]
res[,`:=`(CHROM=as.character(CHROM),
POS=as.numeric(POS),
numCHR=as.numeric(gsub("chr","",as.character(
factor(CHROM,levels=chrs,labels=1:length(chrs))))))]
res <- res[order(numCHR,POS),]
Nmarkers <- nrow(res)
hits <- res[LOG10P >= min(yLine),]
if (!is.null(hitregion)){
candidateRegions <- fread(hitregion,sep="\t",header=T)
candidateRegions[,CHROM:=as.character(CHROM)]
for(r in 1:nrow(candidateRegions)){
rhits <- res[CHROM == candidateRegions$CHROM[r] &
POS >= candidateRegions$START[r] & POS <= candidateRegions$END[r],]
candidateRegions$POS[r] <- rhits$POS[which.max(rhits$LOG10P)]
}
} else if(nrow(hits) > 0){
hits[,`:=`(POS0=POS-1,CHROM=gsub("chr","",CHROM))]
x <- as.numeric(hits$POS)
y <- hits$numCHR
start = c(1, which(diff(y) != 0 | diff(x) <= -regionSize | diff(x) >= regionSize) + 1)
end = c(start - 1, length(x))
candidateRegions <- data.table(
'CHROM'=as.character(hits$CHROM[start]),
'START'=hits$POS[start] - regionSize/2,
'END'=hits$POS[end] + regionSize/2,
'COL'="blue",
'MARKER'=1:length(start),
'POS'=NA)
candidateRegions[START < 1,START:=1]
for(r in 1:nrow(candidateRegions)){
rhits <- hits[CHROM == candidateRegions$CHROM[r] &
POS >= candidateRegions$START[r] & POS <= candidateRegions$END[r],]
candidateRegions$POS[r] <- rhits$POS[which.max(rhits$LOG10P)]
}
if(labelPeaks){
# add nearest GENENAME
candidateRegions <- getNearestGene(input=candidateRegions,Marker="MARKER",chromosome="CHROM",position="POS",build=build)
candidateRegions <- candidateRegions[,.(CHROM,START,END,COL,POS,LABEL,RelativeToGene)]
if(build == "hg38" & grepl("chr", res[1, CHROM])) candidateRegions[,CHROM:=paste0("chr",CHROM)]
} else {
candidateRegions$LABEL <- NA
}
} else {
# empty table if there are no hits
candidateRegions <- data.table(
'CHROM'=character(0),
'START'=numeric(0),
'END'=numeric(0),
'COL'=character(0),
'POS'=numeric(0),
'LABEL'=numeric(0))
}
# Thinning; remove 95% of variants with P > 0.05
thinned <- res[
(LOG10P >= -log10(0.05) & LOG10P <= 6) |
(LOG10P < -log10(0.05) & sample(c(T,rep(F,19)),.N,replace=T)),
.(CHROM,POS,LOG10P,numCHR)]
# Additional thinning using unique after rounding position and p-value
# keep all SNPs with p < 1E-6
plotdata <- rbind(
res[LOG10P > 6,],
thinned[!duplicated(paste(CHROM,round(POS/1000),round(LOG10P,1))),])
plotdata <- plotdata[order(numCHR,POS),.(CHROM,POS,LOG10P,numCHR)]
# Prepare plot data / two-colored chromosomes
plotdata[,`:=`(
pch=20,
highlightColor=as.character(NA),
pcol = ifelse(numCHR %%2 == 0, "grey40","grey60"))]
# covert pos on chromosomes to continuous plot positions
chrGAP <- 1E7
endPos <- 0
plotPos <- numeric(0)
chrLab <- numeric(0)
chrGAP <- 1E7
for(chr in chrs){
chrTemp <- which(plotdata$CHROM == chr)
chrPOS <- plotdata$POS[chrTemp]-min(plotdata$POS[chrTemp],na.rm=T)+endPos+1
chrLab <- c(chrLab,mean(chrPOS,na.rm=T))
endPos <- max(chrPOS,na.rm=T)+chrGAP
plotPos <- c(plotPos,chrPOS)
}
plotdata[,x:=plotPos]
# update numeric non-autosomal chromosome names
chrs <- gsub("chr","",chrs)
fixChr <- c(1:22,"X","Y","XY","MT","X","Y","XY","MT")
names(fixChr) <- c(1:26,"X","Y","XY","MT")
chrs <- fixChr[chrs]
# Highlight candidate regions
if(nrow(candidateRegions)>0){
a <- 0
while(a < nrow(candidateRegions)){
a <- a + 1
if(!coltop){
overlap <- plotdata[CHROM == candidateRegions$CHROM[a] &
POS >= candidateRegions$START[a] &
POS <= candidateRegions$END[a] &
is.na(highlightColor),`:=`
(highlightColor = candidateRegions$COL[a],pcol=NA)]
} else {
overlap <- plotdata[CHROM == candidateRegions$CHROM[a] &
POS >= candidateRegions$START[a] &
POS <= candidateRegions$END[a] &
is.na(highlightColor) &
LOG10P >= min(yLine),`:=`
(highlightColor = candidateRegions$COL[a],pcol=NA)]
}
}
}
# Manhattan plot
par(mar=c(5.1,5.1,4.1,1.1),las=1)
maxY <- plotdata[,max(LOG10P,na.rm=T)]
# Version with two y axes
if(maxY > break.top/(1 - top.size)){
# Manhattan plot with two different y axis scales
# set axis labels for both scales
lab1 <- pretty(c(0,break.top),n=ceiling(12 * (1-top.size)))
lab1 <- c(lab1[lab1 < break.top],break.top)
lab2 <- pretty(c(break.top,maxY),n=max(3,floor(12 * top.size)))
lab2 <- lab2[lab2 > max(lab1)]
lab <- c(lab1,lab2)
# resulting range of top scale in bottom scale units
top.range = break.top/(1 - top.size) - break.top
top.data = max(lab2)-break.top
# function to rescale the top part
rescaleY <- function(y) {
if (y <= break.top) {
y
} else {
break.top + (y - break.top)/(top.data/top.range)
}
}
ylim=c(0,break.top+top.range)
addbreak <- T
} else {
break.top <- maxY
rescaleY <- function(y) y
addbreak <- F
ylim <- c(0,ceiling(max(maxY+1,yLine)))
lab <- pretty(ylim)
lab <- lab[lab < maxY]
}
plotdata[,y:=sapply(LOG10P,rescaleY)]
regionLabels <- merge(plotdata[,.(CHROM,POS,x,y)],
candidateRegions,
by=c("CHROM","POS"),sort=F)
# plot non-highlighted positions
plotdata[,plot(x,y,ylim=ylim,axes=FALSE,
pch=`pch`, cex=0.9,cex.lab=1.5,cex.axis=1.5, xaxt="n",
col=`pcol`, ylab=expression(-log[10]*italic(P)), xlab="",bty="n",
main=gsub("_"," ",paste0(maintitle,"\n",format(Nmarkers,big.mark=",",scientific=F),
" variants")))]
# add axes and axis labels
axis(1,at=chrLab[seq(1,length(chrLab),by=2)],
labels=chrs[1:length(chrLab)][seq(1,length(chrLab),by=2)],
las=1,tick=F,cex.axis=1.5,cex.lab=1.5,line=2)
axis(1,at=chrLab[seq(2,length(chrLab),by=2)],
labels=chrs[1:length(chrLab)][seq(2,length(chrLab),by=2)],
las=1,tick=F,cex.axis=1.5,cex.lab=1.5,line=0)
axis(side=2,at=sapply(lab,rescaleY),labels=lab,cex.axis=1.5,cex.lab=1.5)
if(addbreak){
# plot axis breaks and indicate line of axis break
box()
axis.break(axis=2,breakpos=break.top,style="zigzag",brw=0.02)
axis.break(axis=4,breakpos=break.top,style="zigzag",brw=0.02)
abline(h=break.top,lwd=1.5,lty=2,col="grey")
}
if(length(yLine)>0) abline(h=sapply(yLine,rescaleY),lwd=1.5,col=colLine,lty=2)
# label top regions
if(nrow(regionLabels)>0){
for(hcol in unique(regionLabels$COL)){
plotdata[highlightColor == hcol,points(x,y,pch=20,col=hcol, cex=0.9)]
}
# non-overlapping labels
if(labelPeaks)
regionLabels[,addTextLabels(xCoords = `x`, yCoords = `y`, labels = `LABEL`,
col.label = "black", col.line = t_black, cex.label = 1, col.background = t_white)]
}
return(candidateRegions)
}
option_list <- list(
make_option("--input", type="character", default="",
help="Input file, tab delimited"),
make_option("--prefix", type="character", default="",
help="Prefix of output files"),
make_option("--top.size", type="numeric", default=0.125,
help="top size = proportion of total length y axis [default=0.125]"),
make_option("--break.top", type="numeric", default=15,
help="set axis break at -log10(P) [default=15]"),
make_option("--width", type="numeric", default=1600,
help="Width Manhattan plot in pixel [default=1600]"),
make_option("--height", type="numeric", default=900,
help="Height Manhattan plot in pixel [default=900]"),
make_option("--pointsize", type="numeric", default=16,
help="Point size of plots [default=16]"),
make_option("--hitregion", type="character", default=NULL,
help="File with candidate regions, CHROM;START;END;COL;LABEL [default='']"),
make_option("--flankingsize", type="integer", default=500000,
help="Flanking region to determine candidate regions, top hit +/- X bp [default=500000]"),
make_option("--chr", type="character", default="CHR",
help="name of column with chromosome [default='CHR']"),
make_option("--pos", type="character", default="POS",
help="name of column with position [default='POS']"),
make_option("--pvalue", type="character", default="PVALUE",
help="name of column with p.value [default='PVALUE']"),
make_option("--log10p", type="logical", default=F,
help="Input p.value column with -log10(p.value) [default=F]"),
make_option("--sigthreshold", type="character", default="5E-8",
help="Significance threshold [default=5E-8]"),
make_option("--coltop", type="logical", default=F,
help="Highlight only markers above the significance threshold [default=F]"),
make_option("--maintitle", type="character", default="",
help="Plot title"),
make_option("--build", type="character", default="hg19",
help="Genome build [default='hg19']"),
make_option("--threads", type="numeric", default=1,
help="DTthreads")
)
parser <- OptionParser(usage="%prog [options]", option_list=option_list)
args <- parse_args(parser, positional_arguments = 0)
opt <- args$options
print(opt)
gwas <- fread(opt$input,select=c(opt$chr,opt$pos,opt$pvalue),col.names=c("CHROM","POS","PVALUE"))
png(filename = paste0(opt$prefix,"_Manhattan.png"), width = opt$width, height = opt$height, pointsize = opt$pointsize)
candidateRegions <- ManhattanPlot(res=gwas,top.size=opt$top.size,break.top=opt$break.top,hitregion=opt$hitregion,
regionSize=opt$flankingsize,log10p=opt$log10p,sigthreshold=opt$sigthreshold,coltop=opt$coltop,maintitle=opt$maintitle,
build=opt$build,DTthreads=opt$threads)
dev.off()
if(nrow(candidateRegions) > 0) fwrite(candidateRegions,paste0(opt$prefix,"_ManhattanPlot_",
round(opt$flankingsize/1000),"kb_CandidateRegions.txt"),sep="\t",quote=F)