Mercurial > repos > davidvanzessen > shm_csr
view pattern_plots.r @ 76:a93136637bea draft
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author | davidvanzessen |
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date | Tue, 18 Jun 2019 04:47:44 -0400 |
parents | 1cf60ae234b4 |
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library(ggplot2) library(reshape2) library(scales) args <- commandArgs(trailingOnly = TRUE) input.file = args[1] #the data that's get turned into the "SHM overview" table in the html report "data_sum.txt" plot1.path = args[2] plot1.png = paste(plot1.path, ".png", sep="") plot1.txt = paste(plot1.path, ".txt", sep="") plot1.pdf = paste(plot1.path, ".pdf", sep="") plot2.path = args[3] plot2.png = paste(plot2.path, ".png", sep="") plot2.txt = paste(plot2.path, ".txt", sep="") plot2.pdf = paste(plot2.path, ".pdf", sep="") plot3.path = args[4] plot3.png = paste(plot3.path, ".png", sep="") plot3.txt = paste(plot3.path, ".txt", sep="") plot3.pdf = paste(plot3.path, ".pdf", sep="") clean.output = args[5] dat = read.table(input.file, header=F, sep=",", quote="", stringsAsFactors=F, fill=T, row.names=1) classes = c("IGA", "IGA1", "IGA2", "IGG", "IGG1", "IGG2", "IGG3", "IGG4", "IGM", "IGE") xyz = c("x", "y", "z") new.names = c(paste(rep(classes, each=3), xyz, sep="."), paste("un", xyz, sep="."), paste("all", xyz, sep=".")) names(dat) = new.names clean.dat = dat clean.dat = clean.dat[,c(paste(rep(classes, each=3), xyz, sep="."), paste("all", xyz, sep="."), paste("un", xyz, sep="."))] write.table(clean.dat, clean.output, quote=F, sep="\t", na="", row.names=T, col.names=NA) dat["RGYW.WRCY",] = colSums(dat[c(13,14),], na.rm=T) dat["TW.WA",] = colSums(dat[c(15,16),], na.rm=T) data1 = dat[c("RGYW.WRCY", "TW.WA"),] data1 = data1[,names(data1)[grepl(".z", names(data1))]] names(data1) = gsub("\\..*", "", names(data1)) data1 = melt(t(data1)) names(data1) = c("Class", "Type", "value") chk = is.na(data1$value) if(any(chk)){ data1[chk, "value"] = 0 } data1 = data1[order(data1$Type),] write.table(data1, plot1.txt, quote=F, sep="\t", na="", row.names=F, col.names=T) p = ggplot(data1, aes(Class, value)) + geom_bar(aes(fill=Type), stat="identity", position="dodge", colour = "black") + ylab("% of mutations") + guides(fill=guide_legend(title=NULL)) + ggtitle("Percentage of mutations in AID and pol eta motives") p = p + theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1)) + scale_fill_manual(values=c("RGYW.WRCY" = "white", "TW.WA" = "blue4")) #p = p + scale_colour_manual(values=c("RGYW.WRCY" = "black", "TW.WA" = "blue4")) png(filename=plot1.png, width=510, height=300) print(p) dev.off() ggsave(plot1.pdf, p) data2 = dat[c(1, 5:8),] data2 = data2[,names(data2)[grepl("\\.x", names(data2))]] names(data2) = gsub(".x", "", names(data2)) data2["A/T",] = dat["Targeting of A T (%)",names(dat)[grepl("\\.z", names(dat))]] data2["G/C transitions",] = round(data2["Transitions at G C (%)",] / data2["Number of Mutations (%)",] * 100, 1) data2["mutation.at.gc",] = dat["Transitions at G C (%)",names(dat)[grepl("\\.y", names(dat))]] data2["G/C transversions",] = round((data2["mutation.at.gc",] - data2["Transitions at G C (%)",]) / data2["Number of Mutations (%)",] * 100, 1) data2["G/C transversions",is.nan(unlist(data2["G/C transversions",]))] = 0 data2["G/C transversions",is.infinite(unlist(data2["G/C transversions",]))] = 0 data2["G/C transitions",is.nan(unlist(data2["G/C transitions",]))] = 0 data2["G/C transitions",is.infinite(unlist(data2["G/C transitions",]))] = 0 data2 = melt(t(data2[c("A/T","G/C transitions","G/C transversions"),])) names(data2) = c("Class", "Type", "value") chk = is.na(data2$value) if(any(chk)){ data2[chk, "value"] = 0 } data2 = data2[order(data2$Type),] write.table(data2, plot2.txt, quote=F, sep="\t", na="", row.names=F, col.names=T) p = ggplot(data2, aes(x=Class, y=value, fill=Type)) + geom_bar(position="fill", stat="identity", colour = "black") + scale_y_continuous(labels=percent_format()) + guides(fill=guide_legend(title=NULL)) + ylab("% of mutations") + ggtitle("Relative mutation patterns") p = p + theme(panel.background = element_rect(fill = "white", colour="black"), text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1)) + scale_fill_manual(values=c("A/T" = "blue4", "G/C transversions" = "gray74", "G/C transitions" = "white")) #p = p + scale_colour_manual(values=c("A/T" = "blue4", "G/C transversions" = "gray74", "G/C transitions" = "black")) png(filename=plot2.png, width=480, height=300) print(p) dev.off() ggsave(plot2.pdf, p) data3 = dat[c(5, 6, 8, 17:20),] data3 = data3[,names(data3)[grepl("\\.x", names(data3))]] names(data3) = gsub(".x", "", names(data3)) data3["G/C transitions",] = round(data3["Transitions at G C (%)",] / (data3["C",] + data3["G",]) * 100, 1) data3["G/C transversions",] = round((data3["Targeting of G C (%)",] - data3["Transitions at G C (%)",]) / (data3["C",] + data3["G",]) * 100, 1) data3["A/T",] = round(data3["Targeting of A T (%)",] / (data3["A",] + data3["T",]) * 100, 1) data3["G/C transitions",is.nan(unlist(data3["G/C transitions",]))] = 0 data3["G/C transitions",is.infinite(unlist(data3["G/C transitions",]))] = 0 data3["G/C transversions",is.nan(unlist(data3["G/C transversions",]))] = 0 data3["G/C transversions",is.infinite(unlist(data3["G/C transversions",]))] = 0 data3["A/T",is.nan(unlist(data3["A/T",]))] = 0 data3["A/T",is.infinite(unlist(data3["A/T",]))] = 0 data3 = melt(t(data3[8:10,])) names(data3) = c("Class", "Type", "value") chk = is.na(data3$value) if(any(chk)){ data3[chk, "value"] = 0 } data3 = data3[order(data3$Type),] write.table(data3, plot3.txt, quote=F, sep="\t", na="", row.names=F, col.names=T) p = ggplot(data3, aes(Class, value)) + geom_bar(aes(fill=Type), stat="identity", position="dodge", colour = "black") + ylab("% of nucleotides") + guides(fill=guide_legend(title=NULL)) + ggtitle("Absolute mutation patterns") p = p + theme(panel.background = element_rect(fill = "white", colour="black"), text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1)) + scale_fill_manual(values=c("A/T" = "blue4", "G/C transversions" = "gray74", "G/C transitions" = "white")) #p = p + scale_colour_manual(values=c("A/T" = "blue4", "G/C transversions" = "gray74", "G/C transitions" = "black")) png(filename=plot3.png, width=480, height=300) print(p) dev.off() ggsave(plot3.pdf, p)