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Rfastqc.R
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Rfastqc.R
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rm(list=ls())
getProgramName<-function(){
args <- commandArgs(trailingOnly = FALSE)
sub("--file=", "", args[grep("--file=", args)])
}
program <- getProgramName()
args <- commandArgs(trailingOnly = TRUE)
if (length(args)<2) {
stop(sprintf("Please input the information of arguments:
args[1] outfile
args[2] read1(/share/work1/staff/xuxiong/test/13C37198_L7_I012.R1.clean.fastq.gz)
args[3] read2
Example:
Rscript %s out /share/work1/staff/xuxiong/test/13C37198_L7_I012.R1.clean.fastq.gz
Usage:
Rscript %s outfile read1 [read2]",program,program)
)
}
ptm <- proc.time()
options(scipen=999)
outfile<-args[1]
fastq1<-args[2]
fastq2<-ifelse(length(args)>2,args[3],"")
.libPaths("/home/xuxiong/bin/R_installed_package/")
barplot_Data_range<-function(outfile,Data){
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile,"_read_freq_count",".png",sep=''),pointsize=18,width=900,height=600)
Data_range<-c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,50,100,500)
Data<-as.numeric(Data)
Data_range_count<-sapply(Data_range,function(X){
ifelse(X==max(Data_range),length(Data[Data>=X]),length(Data[Data>=X & Data<Data_range[which(Data_range %in% X)+1]]))
})
# cat(Data_range_count,"\n",file=stderr())
mp <- barplot(Data_range_count,
beside=TRUE,
width = 0.5,
axisnames = F,
cex.names = 0.8,
xlab="Hits range",
ylab="frequency counts",
col=colors[1],
ylim=c(0,max(Data_range_count)*1.2),
axes=TRUE,
plot=TRUE,
xpd=FALSE,
pch=15,
# args.legend = list(x = "topleft"),
main=list("Fastq Hits distribution"),
)
# cat(mp,"\n",axTicks(1),"\n",axTicks(2),"\n",file=stderr())
# cat(sprintf("%.3f%%\n%.3f%%\n",sum(Data_range_count)/sum(Data)*100,(1-Data_range_count[1]/sum(Data))*100),file=stderr())
# cat(paste(round(Data_range_count/sum(Data)*100,3),"%",sep=""),"\n",file=stderr())
text(mp,Data_range_count,
# labels = sapply(Data_range_count,function(x){sprintf("%d\n%.2f%%",x,x/sum(Data)*100)}),
labels = sapply(Data_range_count,function(x){sprintf("%d",x)}),
adj=c(0.5,-0.5), cex=0.6,xpd = TRUE
)
text(mp, par("usr")[3],
labels = sapply(Data_range,function(X){
ifelse(X==max(Data_range),
paste(">=",max(Data_range),sep=""),
ifelse(Data_range[which(Data_range %in% X)+1]-X>1,paste('[',X,',',Data_range[which(Data_range %in% X)+1],')',sep=''),X)
)
}),
srt = 45, adj = c(1,1),cex=0.8,xpd = TRUE
)
#arrows(x0=mp,y0=as.numeric(Data_range_count)*0.95,x1=mp,y1=as.numeric(Data_range_count)*1.05,angle=90,code=3,length=0.04,lwd=1)
box()
pic=dev.off()
cat("Done barplot Data_range\n",file=stderr())
}
plot_Data_range<-function(outfile,Data){
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile,"_dup_level",".png",sep=''),pointsize=18,width=900,height=600)
# Data_range<-c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,50,100,500)
Data_range<-c(1,2,3,4,5,6,7,8,9,10)
Data_range_count<-sapply(Data_range,function(X){
ifelse(X==max(Data_range),
sum(Data[Data>=X]),
sum(Data[Data>=X & Data<Data_range[which(Data_range %in% X)+1]]))
})
Data_range_count_norm<-Data_range_count/Data_range_count[1]*100
# cat(Data_range_count_norm,"\n",file=stderr())
plot(seq_along(Data_range),Data_range_count_norm,
type="l",
xlab="Duplicate level",
ylab="Percentage(%)",
col=colors[1],
axes=TRUE,
# xaxs='r',
xaxt='n',
xpd=FALSE,
ylim=c(0,max(Data_range_count_norm)*1.2),
pch=1,
font.lab=1.2,font.main=2,font.axis=1,lwd=2,
cex.lab=1.5,cex.main=1.5,cex.axis=1,cex.sub=1,cex=0.5,
main=list("Sequence duplication level")
)
axis(1,at=Data_range,
label=sapply(Data_range,function(X){
ifelse(X==max(Data_range),
paste(">=",max(Data_range),sep=""),
ifelse(Data_range[which(Data_range %in% X)+1]-X>1,paste('[',X,',',Data_range[which(Data_range %in% X)+1],')',sep=''),X)
)
}),
srt = 45
)
legend("topright",
legend=sprintf("Dup%%: %.3f%%",(1-Data_range_count[1]/sum(Data))*100),
cex=0.8,
inset = 0.01
)
box()
pic=dev.off()
cat("Done plot Data_range\n",file=stderr())
}
plot_GC_density0<-function(outfile,Data,maxLen){
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile,"_GC_density",".png",sep=''),pointsize=18,width=900,height=600)
# cat("Min: ",min(Data),"\tMax: ",max(Data),sprintf("\tMean GC%%: %.2f%%",mean(Data)*100),"\n",file=stderr())
D_Data<-density(Data*100,n=maxLen)
# cat(D_Data$x,"\n",D_Data$y,"\n",file=stderr())
plot(D_Data,
type="o",
xlab="GC(%)",
ylab="density",
col=colors[1],
axes=TRUE,
# xaxs='r',
# xaxt='n',
xpd=FALSE,
# ylim=c(0,max(Data)*1.2),
pch=1,
font.lab=1.2,font.main=2,font.axis=1,lwd=2,
cex.lab=1.5,cex.main=1.5,cex.axis=1,cex.sub=1,cex=0.5,
main=list("GC density distribution")
)
segments(D_Data$x[D_Data$y==max(D_Data$y)],max(D_Data$y),D_Data$x[D_Data$y==max(D_Data$y)],0,col="black",lwd=1,lty=2)
legend("topright",
legend=c(sprintf("Mean GC%%: %.2f%%",mean(Data)*100),sprintf("Max density GC%%: %.2f%%",D_Data$x[D_Data$y==max(D_Data$y)])),
cex=0.8,
inset = 0.01
)
box()
pic=dev.off()
cat("Done plot_GC_density\n",file=stderr())
}
plot_GC_density<-function(outfile,Data,maxLen){
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile,"_GC_density",".png",sep=''),pointsize=18,width=900,height=600)
# cat("Min: ",min(Data),"\tMax: ",max(Data),sprintf("\tMean GC%%: %.2f%%",mean(Data)*100),"\n",file=stderr())
Dens<-density(Data*100,n=maxLen)
x<-Dens$x
y<-Dens$y
tab<-data.frame(x=x,y=y)
nlmod <- nls(y ~ k/(sqrt(2*pi)*sigma)*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=50,sigma=100,k=0.1) , data = tab)
v <- summary(nlmod)$parameters[,"Estimate"]
plot(tab,
type="o",
xlab="GC(%)",
ylab="Count",
col=colors[1],
axes=TRUE,
# xaxs='r',
# xaxt='n',
xpd=FALSE,
# ylim=c(0,max(Data)*1.2),
pch=1,
font.lab=1.2,font.main=2,font.axis=1,lwd=2,cex.lab=1.5,cex.main=1.5,cex.axis=1,cex.sub=1,cex=0.5,
main=list("GC density distribution")
)
plot(function(x) v[3]/(sqrt(2*pi)*v[2])*exp(-1/2*(x-v[1])^2/v[2]^2),type='o',pch=15,
font.lab=1.2,font.main=2,font.axis=1,lwd=2,cex.lab=1.5,cex.main=1.5,cex.axis=1,cex.sub=1,cex=0.5,
col=colors[2],add=T,xlim=range(tab$x)
)
#segments(D_Data$x[D_Data$y==max(D_Data$y)],max(D_Data$y),D_Data$x[D_Data$y==max(D_Data$y)],0,col="black",lwd=1,lty=2)
legend("topright",
legend=c("GC count per read","Theoretical Distribution"),
cex=0.8,
#fill=TRUE,
col=colors,
lty=c(1,1),
pch=c(1,12),
inset = 0.01
)
box()
pic=dev.off()
cat("Done plot_GC_density\n",file=stderr())
}
matrix.axes <- function(data) {
x <- (1:dim(data)[1] - 1) / (dim(data)[1] - 1);
axis(side=1, at=x, labels=1:dim(data)[1], las=2,cex.axis=0.6);
x <- (1:dim(data)[2] - 1) / (dim(data)[2] - 1);
axis(side=2, at=x, labels=1:dim(data)[2], las=2,cex.axis=0.6);
grid(nx=(dim(data)[1]-1), ny=(dim(data)[2]-1), col="black", lty=1,lwd=0.6);
}
plot_quality<-function(outfile,Data){
library(gplots)
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile,"_quality",".png",sep=''),pointsize=18,width=900,height=600)
# Index<-seq_along(1:nrow(Data))[apply(Data,1,function(X){!all(X==0)})]
M<-t(Data[seq(34,75),])
filled.contour(M, plot.axes=matrix.axes(M),
col=colorpanel(30, "white", "red"),
nlevels=20,
main=paste(outfile,"_quality",sep='')
)
pic=dev.off()
cat("Done plot_quality\n",file=stderr())
}
plot_quality2<-function(outfile,Data){
library(lattice)
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
trellis.device(device="png", filename=paste(outfile,"_quality2",".png",sep=''),pointsize=18,width=900,height=600)
M<-t(Data[seq(34,75),])
rgb.palette <- colorRampPalette(c("white", "blue"), space = "rgb")
my.plot <-levelplot(M, main=paste(outfile,"_quality",sep=''),
xlab="cycle",
ylab="quality score",
col.regions=rgb.palette(1200), cuts=1000, at=seq(0,max(M),l=1000),
pretty=TRUE
)
print(my.plot)
dev.off()
cat("Done plot_quality2\n",file=stderr())
}
plot_boxplot<-function(outfile,Data){
colors <- c('#4682B4','#A0522D','#FF8C00','#87CEEB','#6B8E23','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile,"_boxplotquality",".png",sep=''),pointsize=18,width=900,height=600)
Index<-seq_along(1:nrow(Data))[apply(Data,1,function(X){!all(X==0)})]
M<-Data[seq(34,75),]
sumQ30=sum(as.numeric(Data[Index[Index>63],]))
sumQ20=sum(as.numeric(Data[Index[Index>53],]))
sumQ=sum(as.numeric(M))
# cat(sprintf("Q30: %.3f%%(%.0f/%.0f)\nQ20: %.3f%%\n",100*sumQ30/sumQ,sumQ30,sumQ,100*sumQ20/sumQ),file=stderr())
cat(sprintf("Q30: %.3f%%\nQ20: %.3f%%\n",100*sumQ30/sumQ,100*sumQ20/sumQ),file=stderr())
rownames(M)<-seq(0,41)
# print(Index)
boxplot(apply(M,2,function(X){rep(seq(34,75),X%/%100)}),
main=paste(outfile,"_quality",sep=''),
xlab="cycle",
ylab="quality score",
# names=colnames(RPKM),
show.names=T,
varWidth=T,
notch=F,
outline=F,
col=colors[1],
plot=TRUE,
las=0,
boxwex=0.75,
ylim=c(34,75),
# ylim=range(Index),
cex.lab=1,cex.main=1.5,cex.axis=0.8,cex.sub=1,cex=0.5,
font.lab=1,font.main=2,font.axis=0.8,lwd=1,
pch=1
)
pic=dev.off()
cat("Done boxplot_quality\n",file=stderr())
}
draw_length_distribution<-function(outfile_prefix,Len){
png(paste(outfile_prefix,"len.png",sep='_'),pointsize=18,width=900,height=600)
colors <- c('#4682B4','#87CEEB','#6B8E23','#A0522D','#FF8C00','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
totalBase<-sprintf("Total base: %.0f",sum(as.numeric(as.numeric(names(Len))*Len)))
totalReads<-sprintf("Total reads: %.0f",sum(as.numeric(Len)))
meanLen<-sprintf("Mean length: %.1f",weighted.mean(as.numeric(names(Len)), Len))
cat(totalBase,totalReads,meanLen,"\n",file=stderr())
# print(Len)
mp <- barplot(Len,
# beside=TRUE,
width = 1,
names.arg=names(Len),
axisnames = T,
cex.names = 0.8,
cex.axis = 0.8,
xlab="length(bp)",
ylab="Counts",
col=colors[1],
ylim=c(0,max(Len)*1.4),
axes=TRUE,
plot=TRUE,
xpd=FALSE,
pch=15,
args.legend = names(Len),
main=list("Length distribution"),
)
# text(mp,Len,
# labels = sprintf("%d\n(%.2f%%)",Len,Len/sum_count*100),
# adj=c(0.5,-0.5),
# cex=0.75,
# xpd = TRUE
# )
# arrows(x0=mp,y0=Len*0.95,x1=mp,y1=Len*1.05,angle=90,code=3,length=0.04,lwd=0.4)
# text(mp, par("usr")[3],labels = names(Len),srt = 35, cex=0.6,adj = c(1,1),xpd = TRUE)
legend("topleft",
legend=c(totalBase,meanLen,totalReads),
cex=0.8,
col=colors[1],
# lty=1,
# lwd=3,
# fill=colors[1],
# pch=c(1,20),
inset = 0.01
)
box()
pic=dev.off()
cat("Done Length distribution\n",file=stderr())
}
draw_nucleotide_distribution<-function(outfile_prefix,Data){
colors <- c('#4682B4','#87CEEB','#6B8E23','#A0522D','#FF8C00','#6A5ACD','#778899','#DAA520','#B22222','#FF6699')
png(paste(outfile_prefix,'_nucleotide.png',sep=''),pointsize=18,width=900,height=600)
par(mar=c(5.1,4.1,4.1,2.1))
plot(1:ncol(Data),Data[1,],
type="n",
xlab="Cycle",
ylab="Counts",
col=colors,
axes=TRUE,
# xaxs='r',
# xaxt='n',
xpd=T,
ylim=c(0,max(Data)*1.5),
# xlim=c(0,100),
pch=1,
font.lab=1.2,font.main=2,font.axis=1,lwd=2,
cex.lab=1.5,cex.main=1.5,cex.axis=0.8,cex.sub=1,cex=0.5,
main=list("Nucleotide Content Distribution")
)
sapply(1:nrow(Data),function(X){
lines(1:ncol(Data),Data[X,],lwd=2,col=colors[X],type = "o",pch=20)
})
legend("topright",
legend=c("T","C","A","G","N"),
cex=0.8,
col=colors,
lty=1,
lwd=3,
# fill=colors[c(1,2)],
pch=20,
inset = 0.01
)
pic=dev.off()
cat("Done nucleotide distribution\n",file=stderr())
}
dyn.load(paste(dirname(program),ifelse(grepl('Linux|Darwin',Sys.info()["sysname"],perl=T),"Rgzfastq_uniq_3.so","Rgzfastq_uniq_3.dll"),sep="/"))
List<-.Call("qsort_hash_count",fastq1,fastq2)
barplot_Data_range(outfile,List[[1]])
plot_Data_range(outfile,List[[1]])
plot_GC_density(paste(outfile,"R1",sep=""),List[[2]],max(as.numeric(names(List[[5]][List[[5]]>0]))))
List[[3]]<-List[[3]][,apply(List[[3]],2,function(Y){!all(Y==0)})]
#plot_quality(paste(outfile,"R1",sep=""),List[[3]])
plot_quality2(paste(outfile,"R1",sep=""),List[[3]])
plot_boxplot(paste(outfile,"R1",sep=""),List[[3]])
List[[4]]<-List[[4]][,apply(List[[4]],2,function(Y){!all(Y==0)})]
draw_nucleotide_distribution(paste(outfile,"R1",sep=""),List[[4]])
draw_length_distribution(paste(outfile,"R1",sep=""),List[[5]][List[[5]]>0])
if (length(args)>2) {
plot_GC_density(paste(outfile,"R2",sep=""),List[[6]],max(as.numeric(names(List[[9]][List[[9]]>0]))));
List[[7]]<-List[[7]][,apply(List[[7]],2,function(Y){!all(Y==0)})]
# plot_quality(paste(outfile,"R2",sep=""),List[[7]])
plot_quality2(paste(outfile,"R2",sep=""),List[[7]])
plot_boxplot(paste(outfile,"R2",sep=""),List[[7]])
List[[8]]<-List[[8]][,apply(List[[8]],2,function(Y){!all(Y==0)})]
draw_nucleotide_distribution(paste(outfile,"R2",sep=""),List[[8]])
draw_length_distribution(paste(outfile,"R2",sep=""),List[[9]][List[[9]]>0])
}