Mercurial > repos > rhpvorderman > shm_csr

annotate pattern_plots.r @ 0:64d74ba01a7c draft

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"planemo upload commit 78d1fae87dbcf490e49a9f99e7a06de7328e16d4"
author rhpvorderman
date Wed, 27 Oct 2021 12:34:47 +0000
parents
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1 library(ggplot2)
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2 library(reshape2)
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3 library(scales)
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4
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5 args <- commandArgs(trailingOnly = TRUE)
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6
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7 input.file = args[1] #the data that's get turned into the "SHM overview" table in the html report "data_sum.txt"
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8
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9 plot1.path = args[2]
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10 plot1.png = paste(plot1.path, ".png", sep="")
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11 plot1.txt = paste(plot1.path, ".txt", sep="")
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12 plot1.pdf = paste(plot1.path, ".pdf", sep="")
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13
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14 plot2.path = args[3]
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15 plot2.png = paste(plot2.path, ".png", sep="")
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16 plot2.txt = paste(plot2.path, ".txt", sep="")
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17 plot2.pdf = paste(plot2.path, ".pdf", sep="")
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18
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19 plot3.path = args[4]
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20 plot3.png = paste(plot3.path, ".png", sep="")
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21 plot3.txt = paste(plot3.path, ".txt", sep="")
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22 plot3.pdf = paste(plot3.path, ".pdf", sep="")
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23
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24 clean.output = args[5]
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25
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26 dat = read.table(input.file, header=F, sep=",", quote="", stringsAsFactors=F, fill=T, row.names=1)
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28 classes = c("IGA", "IGA1", "IGA2", "IGG", "IGG1", "IGG2", "IGG3", "IGG4", "IGM", "IGE")
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29 xyz = c("x", "y", "z")
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30 new.names = c(paste(rep(classes, each=3), xyz, sep="."), paste("un", xyz, sep="."), paste("all", xyz, sep="."))
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31
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32 names(dat) = new.names
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34 clean.dat = dat
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35 clean.dat = clean.dat[,c(paste(rep(classes, each=3), xyz, sep="."), paste("all", xyz, sep="."), paste("un", xyz, sep="."))]
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36
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37 write.table(clean.dat, clean.output, quote=F, sep="\t", na="", row.names=T, col.names=NA)
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38
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39 dat["RGYW.WRCY",] = colSums(dat[c(14,15),], na.rm=T)
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40 dat["TW.WA",] = colSums(dat[c(16,17),], na.rm=T)
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41
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42 data1 = dat[c("RGYW.WRCY", "TW.WA"),]
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44 data1 = data1[,names(data1)[grepl(".z", names(data1))]]
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45 names(data1) = gsub("\\..*", "", names(data1))
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46
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47 data1 = melt(t(data1))
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48
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49 names(data1) = c("Class", "Type", "value")
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50
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51 chk = is.na(data1$value)
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52 if(any(chk)){
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53 data1[chk, "value"] = 0
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54 }
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55
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56 data1 = data1[order(data1$Type),]
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57
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58 write.table(data1, plot1.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
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59
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60 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")
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61 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"))
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62 #p = p + scale_colour_manual(values=c("RGYW.WRCY" = "black", "TW.WA" = "blue4"))
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63 png(filename=plot1.png, width=510, height=300)
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64 print(p)
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65 dev.off()
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66
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67 ggsave(plot1.pdf, p)
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68
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69 data2 = dat[c(1, 5:8),]
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70
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71 data2 = data2[,names(data2)[grepl("\\.x", names(data2))]]
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72 names(data2) = gsub(".x", "", names(data2))
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73
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74 data2["A/T",] = dat["Targeting of A T (%)",names(dat)[grepl("\\.z", names(dat))]]
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75
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76 data2["G/C transitions",] = round(data2["Transitions at G C (%)",] / data2["Number of Mutations (%)",] * 100, 1)
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77
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78 data2["mutation.at.gc",] = dat["Transitions at G C (%)",names(dat)[grepl("\\.y", names(dat))]]
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79 data2["G/C transversions",] = round((data2["mutation.at.gc",] - data2["Transitions at G C (%)",]) / data2["Number of Mutations (%)",] * 100, 1)
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80
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81 data2["G/C transversions",is.nan(unlist(data2["G/C transversions",]))] = 0
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82 data2["G/C transversions",is.infinite(unlist(data2["G/C transversions",]))] = 0
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83 data2["G/C transitions",is.nan(unlist(data2["G/C transitions",]))] = 0
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84 data2["G/C transitions",is.infinite(unlist(data2["G/C transitions",]))] = 0
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85
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86 data2 = melt(t(data2[c("A/T","G/C transitions","G/C transversions"),]))
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87
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88 names(data2) = c("Class", "Type", "value")
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89
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90 chk = is.na(data2$value)
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91 if(any(chk)){
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92 data2[chk, "value"] = 0
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93 }
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94
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95 data2 = data2[order(data2$Type),]
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96
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97 write.table(data2, plot2.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
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98
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99 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")
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100 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"))
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101 #p = p + scale_colour_manual(values=c("A/T" = "blue4", "G/C transversions" = "gray74", "G/C transitions" = "black"))
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102 png(filename=plot2.png, width=480, height=300)
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103 print(p)
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104 dev.off()
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105
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106 ggsave(plot2.pdf, p)
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107
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108 data3 = dat[c(5, 6, 8, 18:21),]
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109 data3 = data3[,names(data3)[grepl("\\.x", names(data3))]]
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110 names(data3) = gsub(".x", "", names(data3))
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111
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112 data3["G/C transitions",] = round(data3["Transitions at G C (%)",] / (data3["C",] + data3["G",]) * 100, 1)
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113
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114 data3["G/C transversions",] = round((data3["Targeting of G C (%)",] - data3["Transitions at G C (%)",]) / (data3["C",] + data3["G",]) * 100, 1)
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115
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116 data3["A/T",] = round(data3["Targeting of A T (%)",] / (data3["A",] + data3["T",]) * 100, 1)
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117
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118 data3["G/C transitions",is.nan(unlist(data3["G/C transitions",]))] = 0
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119 data3["G/C transitions",is.infinite(unlist(data3["G/C transitions",]))] = 0
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120
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121 data3["G/C transversions",is.nan(unlist(data3["G/C transversions",]))] = 0
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122 data3["G/C transversions",is.infinite(unlist(data3["G/C transversions",]))] = 0
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123
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124 data3["A/T",is.nan(unlist(data3["A/T",]))] = 0
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125 data3["A/T",is.infinite(unlist(data3["A/T",]))] = 0
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126
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127 data3 = melt(t(data3[8:10,]))
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128 names(data3) = c("Class", "Type", "value")
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129
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130 chk = is.na(data3$value)
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131 if(any(chk)){
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132 data3[chk, "value"] = 0
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133 }
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134
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135 data3 = data3[order(data3$Type),]
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136
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137 write.table(data3, plot3.txt, quote=F, sep="\t", na="", row.names=F, col.names=T)
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138
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139 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")
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140 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"))
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141 #p = p + scale_colour_manual(values=c("A/T" = "blue4", "G/C transversions" = "gray74", "G/C transitions" = "black"))
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142 png(filename=plot3.png, width=480, height=300)
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143 print(p)
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144 dev.off()
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145
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146 ggsave(plot3.pdf, p)
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