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1 args <- commandArgs(trailingOnly = TRUE)
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2
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3 input = args[1]
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4 summaryinput = args[2]
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5 outputdir = args[3]
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6 setwd(outputdir)
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7
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8 #dat = read.table("NWK276_MID6_25NT/8_V-REGION-nt-mutation-statistics_NWK276_MID6_25NT_051113.txt", header=T, sep="\t", fill=T, stringsAsFactors=F)
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9 dat = read.table(input, header=T, sep="\t", fill=T, stringsAsFactors=F)
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10
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11 datSum = read.table(summaryinput, header=T, sep="\t", fill=T, stringsAsFactors=F)
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12 datSum = datSum[,c("Sequence.ID", "AA.JUNCTION")]
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13
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14 dat = merge(dat, datSum, by="Sequence.ID", all.x=T)
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15
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16 #dat = dat[dat$Functionality == "productive",]
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17
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18 dat$VGene = gsub("^Homsap ", "", dat$V.GENE.and.allele)
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19 dat$VGene = gsub("[*].*", "", dat$VGene)
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20
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21 dat$past = paste(dat$AA.JUNCTION, dat$VGene)
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22
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23 #dat = dat[!duplicated(dat$past), ]
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24
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25 if(length(dat$Sequence.ID) == 0){
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26 setwd(outputdir)
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27 result = data.frame(x = rep(0, 5), y = rep(0, 5), z = rep(NA, 5))
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28 row.names(result) = c("Number of Mutations (%)", "Transition (%)", "Transversions (%)", "Transitions at G C (%)", "Targeting of C G (%)")
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29 write.table(x=result, file="mutations.txt", sep=",",quote=F,row.names=T,col.names=F)
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30 transitionTable = data.frame(A=rep(0, 4),C=rep(0, 4),G=rep(0, 4),T=rep(0, 4))
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31 row.names(transitionTable) = c("A", "C", "G", "T")
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32 transitionTable["A","A"] = NA
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33 transitionTable["C","C"] = NA
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34 transitionTable["G","G"] = NA
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35 transitionTable["T","T"] = NA
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36 write.table(x=transitionTable, file="transitions.txt", sep=",",quote=F,row.names=T,col.names=NA)
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37 cat("0", file="n.txt")
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38 stop("No data")
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39 }
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40
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41 #print(paste("After filtering on 'productive' and deduplicating based on V and AA JUNCTION there are", length(dat$Sequence.ID), "sequences left"))
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42
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43 result = data.frame(x = 1:5, y = 1:5, z = 1:5)
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44 row.names(result) = c("Number of Mutations (%)", "Transition (%)", "Transversions (%)", "Transitions at G C (%)", "Targeting of C G (%)")
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45
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46 cleanup_columns = c("FR1.IMGT.c.a",
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47 "FR2.IMGT.g.t",
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48 "CDR1.IMGT.Nb.of.nucleotides",
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49 "CDR2.IMGT.t.a",
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50 "FR1.IMGT.c.g",
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51 "CDR1.IMGT.c.t",
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52 "FR2.IMGT.a.c",
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53 "FR2.IMGT.Nb.of.mutations",
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54 "FR2.IMGT.g.c",
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55 "FR2.IMGT.a.g",
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56 "FR3.IMGT.t.a",
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57 "FR3.IMGT.t.c",
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58 "FR2.IMGT.g.a",
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59 "FR3.IMGT.c.g",
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60 "FR1.IMGT.Nb.of.mutations",
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61 "CDR1.IMGT.g.a",
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62 "CDR1.IMGT.t.g",
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63 "CDR1.IMGT.g.c",
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64 "CDR2.IMGT.Nb.of.nucleotides",
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65 "FR2.IMGT.a.t",
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66 "CDR1.IMGT.Nb.of.mutations",
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67 "CDR1.IMGT.a.g",
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68 "FR3.IMGT.a.c",
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69 "FR1.IMGT.g.a",
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70 "FR3.IMGT.a.g",
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71 "FR1.IMGT.a.t",
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72 "CDR2.IMGT.a.g",
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73 "CDR2.IMGT.Nb.of.mutations",
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74 "CDR2.IMGT.g.t",
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75 "CDR2.IMGT.a.c",
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76 "CDR1.IMGT.t.c",
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77 "FR3.IMGT.g.c",
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78 "FR1.IMGT.g.t",
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79 "FR3.IMGT.g.t",
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80 "CDR1.IMGT.a.t",
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81 "FR1.IMGT.a.g",
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82 "FR3.IMGT.a.t",
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83 "FR3.IMGT.Nb.of.nucleotides",
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84 "FR2.IMGT.t.c",
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85 "CDR2.IMGT.g.a",
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86 "FR2.IMGT.t.a",
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87 "CDR1.IMGT.t.a",
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88 "FR2.IMGT.t.g",
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89 "FR3.IMGT.t.g",
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90 "FR2.IMGT.Nb.of.nucleotides",
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91 "FR1.IMGT.t.a",
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92 "FR1.IMGT.t.g",
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93 "FR3.IMGT.c.t",
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94 "FR1.IMGT.t.c",
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95 "CDR2.IMGT.a.t",
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96 "FR2.IMGT.c.t",
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97 "CDR1.IMGT.g.t",
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98 "CDR2.IMGT.t.g",
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99 "FR1.IMGT.Nb.of.nucleotides",
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100 "CDR1.IMGT.c.g",
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101 "CDR2.IMGT.t.c",
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102 "FR3.IMGT.g.a",
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103 "CDR1.IMGT.a.c",
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104 "FR2.IMGT.c.a",
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105 "FR3.IMGT.Nb.of.mutations",
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106 "FR2.IMGT.c.g",
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107 "CDR2.IMGT.g.c",
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108 "FR1.IMGT.g.c",
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109 "CDR2.IMGT.c.t",
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110 "FR3.IMGT.c.a",
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111 "CDR1.IMGT.c.a",
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112 "CDR2.IMGT.c.g",
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113 "CDR2.IMGT.c.a",
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114 "FR1.IMGT.c.t")
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115
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116 for(col in cleanup_columns){
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117 dat[,col] = gsub("\\(.*\\)", "", dat[,col])
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118 #dat[dat[,col] == "",] = "0"
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119 dat[,col] = as.numeric(dat[,col])
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120 dat[is.na(dat[,col]),] = 0
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121 }
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122
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123 VRegionMutations = sum(dat$FR1.IMGT.Nb.of.mutations +
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124 dat$CDR1.IMGT.Nb.of.mutations +
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125 dat$FR2.IMGT.Nb.of.mutations +
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126 dat$CDR2.IMGT.Nb.of.mutations +
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127 dat$FR3.IMGT.Nb.of.mutations)
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128
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129 VRegionNucleotides = sum( dat$FR1.IMGT.Nb.of.nucleotides +
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130 dat$CDR1.IMGT.Nb.of.nucleotides +
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131 dat$FR2.IMGT.Nb.of.nucleotides +
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132 dat$CDR2.IMGT.Nb.of.nucleotides +
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133 dat$FR3.IMGT.Nb.of.nucleotides)
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134
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135 result[1,"x"] = VRegionMutations
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136 result[1,"y"] = VRegionNucleotides
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137 result[1,"z"] = round(result[1,"x"] / result[1,"y"] * 100, digits=1)
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138
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139 transitionMutations = sum(dat$FR1.IMGT.a.g +
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140 dat$FR1.IMGT.g.a +
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141 dat$FR1.IMGT.c.t +
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142 dat$FR1.IMGT.t.c +
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143 dat$CDR1.IMGT.a.g +
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144 dat$CDR1.IMGT.g.a +
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145 dat$CDR1.IMGT.c.t +
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146 dat$CDR1.IMGT.t.c +
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147 dat$FR2.IMGT.a.g +
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148 dat$FR2.IMGT.g.a +
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149 dat$FR2.IMGT.c.t +
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150 dat$FR2.IMGT.t.c +
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151 dat$CDR2.IMGT.a.g +
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152 dat$CDR2.IMGT.g.a +
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153 dat$CDR2.IMGT.c.t +
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154 dat$CDR2.IMGT.t.c +
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155 dat$FR3.IMGT.a.g +
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156 dat$FR3.IMGT.g.a +
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157 dat$FR3.IMGT.c.t +
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158 dat$FR3.IMGT.t.c)
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159
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160 result[2,"x"] = transitionMutations
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161 result[2,"y"] = VRegionMutations
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162 result[2,"z"] = round(result[2,"x"] / result[2,"y"] * 100, digits=1)
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163
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164 transversionMutations = sum( dat$FR1.IMGT.a.c +
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165 dat$FR1.IMGT.c.a +
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166 dat$FR1.IMGT.a.t +
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167 dat$FR1.IMGT.t.a +
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168 dat$FR1.IMGT.g.c +
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169 dat$FR1.IMGT.c.g +
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170 dat$FR1.IMGT.g.t +
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171 dat$FR1.IMGT.t.g +
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172 dat$CDR1.IMGT.a.c +
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173 dat$CDR1.IMGT.c.a +
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174 dat$CDR1.IMGT.a.t +
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175 dat$CDR1.IMGT.t.a +
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176 dat$CDR1.IMGT.g.c +
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177 dat$CDR1.IMGT.c.g +
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178 dat$CDR1.IMGT.g.t +
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179 dat$CDR1.IMGT.t.g +
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180 dat$FR2.IMGT.a.c +
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181 dat$FR2.IMGT.c.a +
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182 dat$FR2.IMGT.a.t +
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183 dat$FR2.IMGT.t.a +
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184 dat$FR2.IMGT.g.c +
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185 dat$FR2.IMGT.c.g +
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186 dat$FR2.IMGT.g.t +
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187 dat$FR2.IMGT.t.g +
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188 dat$CDR2.IMGT.a.c +
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189 dat$CDR2.IMGT.c.a +
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190 dat$CDR2.IMGT.a.t +
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191 dat$CDR2.IMGT.t.a +
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192 dat$CDR2.IMGT.g.c +
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193 dat$CDR2.IMGT.c.g +
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194 dat$CDR2.IMGT.g.t +
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195 dat$CDR2.IMGT.t.g +
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196 dat$FR3.IMGT.a.c +
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197 dat$FR3.IMGT.c.a +
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198 dat$FR3.IMGT.a.t +
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199 dat$FR3.IMGT.t.a +
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200 dat$FR3.IMGT.g.c +
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201 dat$FR3.IMGT.c.g +
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202 dat$FR3.IMGT.g.t +
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203 dat$FR3.IMGT.t.g)
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204
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205 result[3,"x"] = transversionMutations
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206 result[3,"y"] = VRegionMutations
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207 result[3,"z"] = round(result[3,"x"] / result[3,"y"] * 100, digits=1)
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208
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209 transitionMutationsAtGC = sum(dat$FR1.IMGT.g.a +
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210 dat$FR1.IMGT.c.t +
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211 dat$CDR1.IMGT.g.a +
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212 dat$CDR1.IMGT.c.t +
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213 dat$FR2.IMGT.g.a +
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214 dat$FR2.IMGT.c.t +
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215 dat$CDR2.IMGT.g.a +
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216 dat$CDR2.IMGT.c.t +
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217 dat$FR3.IMGT.g.a +
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218 dat$FR3.IMGT.c.t)
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219
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220 totalMutationsAtGC = sum(dat$FR1.IMGT.g.a +
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221 dat$FR1.IMGT.c.t +
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222 dat$FR1.IMGT.c.a +
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223 dat$FR1.IMGT.g.c +
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224 dat$FR1.IMGT.c.g +
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225 dat$FR1.IMGT.g.t +
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226 dat$CDR1.IMGT.g.a +
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227 dat$CDR1.IMGT.c.t +
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228 dat$CDR1.IMGT.c.a +
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229 dat$CDR1.IMGT.g.c +
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230 dat$CDR1.IMGT.c.g +
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231 dat$CDR1.IMGT.g.t +
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232 dat$FR2.IMGT.g.a +
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233 dat$FR2.IMGT.c.t +
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234 dat$FR2.IMGT.c.a +
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235 dat$FR2.IMGT.g.c +
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236 dat$FR2.IMGT.c.g +
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237 dat$FR2.IMGT.g.t +
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238 dat$CDR2.IMGT.g.a +
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239 dat$CDR2.IMGT.c.t +
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240 dat$CDR2.IMGT.c.a +
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241 dat$CDR2.IMGT.g.c +
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242 dat$CDR2.IMGT.c.g +
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243 dat$CDR2.IMGT.g.t +
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244 dat$FR3.IMGT.g.a +
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245 dat$FR3.IMGT.c.t +
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246 dat$FR3.IMGT.c.a +
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247 dat$FR3.IMGT.g.c +
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248 dat$FR3.IMGT.c.g +
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249 dat$FR3.IMGT.g.t)
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250
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251 result[4,"x"] = transitionMutationsAtGC
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252 result[4,"y"] = totalMutationsAtGC
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253 result[4,"z"] = round(result[4,"x"] / result[4,"y"] * 100, digits=1)
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254
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255 result[5,"x"] = totalMutationsAtGC
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256 result[5,"y"] = VRegionMutations
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257 result[5,"z"] = round(result[5,"x"] / result[5,"y"] * 100, digits=1)
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258
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259
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260 #transitiontable
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261
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262 transitionTable = data.frame(A=1:4,C=1:4,G=1:4,T=1:4)
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263 row.names(transitionTable) = c("A", "C", "G", "T")
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264 transitionTable["A","A"] = NA
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265 transitionTable["C","C"] = NA
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266 transitionTable["G","G"] = NA
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267 transitionTable["T","T"] = NA
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268 nts = c("a", "c", "g", "t")
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269
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270
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271 for(nt1 in nts){
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272 for(nt2 in nts){
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273 if(nt1 == nt2){
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274 next
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275 }
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276 NT1 = LETTERS[letters == nt1]
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277 NT2 = LETTERS[letters == nt2]
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278 FR1 = paste("FR1.IMGT.", nt1, ".", nt2, sep="")
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279 CDR1 = paste("CDR1.IMGT.", nt1, ".", nt2, sep="")
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280 FR2 = paste("FR2.IMGT.", nt1, ".", nt2, sep="")
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281 CDR2 = paste("CDR2.IMGT.", nt1, ".", nt2, sep="")
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282 FR3 = paste("FR3.IMGT.", nt1, ".", nt2, sep="")
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283 transitionTable[NT1,NT2] = sum( dat[,FR1] +
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284 dat[,CDR1] +
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285 dat[,FR2] +
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286 dat[,CDR2] +
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287 dat[,FR3])
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288 }
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289 }
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290
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291 setwd(outputdir)
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292 write.table(x=result, file="mutations.txt", sep=",",quote=F,row.names=T,col.names=F)
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293 write.table(x=transitionTable, file="transitions.txt", sep=",",quote=F,row.names=T,col.names=NA)
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294 cat(length(dat$Sequence.ID), file="n.txt")
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295
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296
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297
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