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1 #!/usr/bin/env Rscript
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2
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3 # rm(list=ls())
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4
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5 library("getopt")
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6
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7 #input from trailing line arguments
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8 args <- commandArgs(trailingOnly = TRUE)
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9 #read the options from input commandArgs
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10 option_specification = matrix(c(
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11 'inf','i01',1,'character',
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12 'itype','i02',2,'character',
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13 'thrup','i03',2,'double',
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14 'thrlow','i04',2,'double',
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15 'allr','i05',2,'character',
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16 'complex','i06',2,'logical',
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17 'lsp','i07',2,'double',
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18 'pcol','i08',2,'character',
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19 'lcol','i09',2,'character',
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20
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21 'xstand','i10',2,'logical',
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22 'bsize','i11',2,'integer',
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23 'bnorm','i12',2,'logical',
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24 'exclthr','i13',2,'double',
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25 'exclcol','i14',2,'character',
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26
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27 'parn','o1',2,'character',
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28 'outn','o2',2,'character',
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29 'pdfn','o3',2,'character'
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30 ), byrow=TRUE, ncol=4)
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31
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32 #parse options
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33 options = getopt(option_specification)
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34
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35 # #FOR DEBUGGING
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36 # options<-NULL
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37 # ###INPUT FILE
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38 # setwd("D:/Dropbox/_galaxy/")
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39 # options$inf<-"nor22.vcf"
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40 # ###BASE OPTIONS
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41 # #interval type
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42 # options$itype<-"C.elegans"
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43 # #user interval type
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44 # options$userif<-NULL
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45 # #quality filter
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46 # options$qual<-200
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47 # #for scaling 0-1 = upper threshold for what is considered homozygous
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48 # options$thrup<-1
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49 # #for scaling 0-1 = lower threshold for what is considered homozygous
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50 # options$thrlow<-0
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51 # #type of allelic ratio (AB/ratio)+---------------------------------------------------------
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52 # options$allr<-"AB"
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53 # #include complex variants
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54 # options$complex<-FALSE
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55 # ###ADDITIONAL VARIANT EXCLUSION OPTIONS
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56 # #files with variants to exclude
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57 # options$exclf<-NULL
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58 # options$exclf<-c("nor22chunk1.txt","nor22chunk5.txt")
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59 # #for variants to exclude, bottom threshold for which to be used, i.e. 0=ALL, 1=HOM only, 0.8=near HOM)
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60 # options$exclthr<-0
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61 # #additional colour option for pre-subtraction line
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62 # options$exclcol<-"green"
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63 # ###PLOT OPTIONS
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64 # #loess span
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65 # options$lsp<-0.4
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66 # #point colour
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67 # options$pcol<-"black"
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68 # #loess plot colour
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69 # options$lcol<-"red"
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70 # #standardize x-axis interval (e.g. 1Mb interval)
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71 # options$xstand<-TRUE
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72 # #bin size for barplot
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73 # options$bsize<-1000000
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74 # #normalization for barplot
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75 # options$bnorm<-FALSE
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76 # ###OUTPUT OPTIONS
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77 # #custom files names (may not work for Galaxy)
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78 # options$outn<-paste(gsub("vcf","",options$inf),"_output_q",options$qual,"-",paste(options$exclf,sep="",collapse=""),".txt",sep="")
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79 # options$parn<-paste(gsub("vcf","",options$inf),"_parsed_q",options$qual,"-",paste(options$exclf,sep="",collapse=""),".txt",sep="")
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80 # options$pdfn<-paste(gsub("vcf","",options$inf),"_plot_q",options$qual,"-",paste(options$exclf,sep="",collapse=""),".pdf",sep="")
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81 # #fixed file names (will work in Galaxy)
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82 # # options$outn<-"vcf_output.txt"
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83 # # options$parn<-"vcf_parsedinput.txt"
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84 # # options$pdfn<-"vdm_mapping_plot.pdf"
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85
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86
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87 'inf','i01',1,'character',
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88 'itype','i02',2,'character',
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89 'qual','i03',2,'double',
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90 'thrup','i04',2,'double',
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91 'thrlow','i05',2,'double',
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92 'allr','i06',2,'character',
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93 'complex','i07',2,'logical',
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94 'lsp','i08',2,'double',
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95 'pcol','i09',2,'character',
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96 'lcol','i10',2,'character',
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97
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98 'xstand','i11',2,'logical',
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99 'bsize','i12',2,'integer',
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100 'bnorm','i13',2,'logical',
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101 'exclthr','i14',2,'double',
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102 'exclcol','i15',2,'character',
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103
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104 'parn','o1',2,'character',
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105 'outn','o2',2,'character',
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106 'pdfn','o3',2,'character'
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107
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108
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109 myfunction<-function(inf,itype,thrup,thrlow,allr,complex,lsp,pcol,lcol,xstand,bsize,bnorm,exclthr,exclcol,parn,outn,pdfn){
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110
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111 #PARAMETERS
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112 # filename<-options$inf
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113 # interval_type<-options$itype
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114 # user_interval_file<-options$userif
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115 # read_qual<-options$qual
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116 # threshold_upper<-options$thrup
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117 # threshold_lower<-options$thrlow
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118 # allele_ratio<-options$allr
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119 # incl_complex<-options$complex
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120 # loess_span<-options$lsp
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121 # plot_color<-options$pcol
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122 # loess_color<-options$lcol
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123 # #transparency for selected colour (to see plot points underneath)
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124 # xaxis_standard<-options$xstand
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125 # bin_size<-options$bsize
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126 # bfreq_norm<-options$bnorm
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127 # exclusion_list<-options$exclf
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128 # excl_threshold<-options$exclthr
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129 # excl_loess_color<-options$exclcol
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130 # vcfoutput_filename<-options$outn
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131 # vcfparsed_filename<-options$parn
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132 # pdf_filename<-options$pdfn
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133
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134 # plot_color<-rgb(c(col2rgb(plot_color)[1]),c(col2rgb(plot_color)[2]),c(col2rgb(plot)[3]),max=255,alpha=150)
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135 # loess_color<-rgb(c(col2rgb(loess_color)[1]),c(col2rgb(loess_color)[2]),c(col2rgb(loess_color)[3]),max=255,alpha=150)
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136 # excl_loess_color<-rgb(c(col2rgb(excl_loess_color)[1]),c(col2rgb(excl_loess_color)[2]),c(col2rgb(excl_loess_color)[3]),max=255,alpha=150)
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137
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138 inf,itype,thrup,thrlow,allr,complex,lsp,pcol,lcol,xstand,bsize,bnorm,exclthr,exclcol,parn,outn,pdfn
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139
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140 filename<-inf
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141 interval_type<-itype
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142 # user_interval_file<-userif
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143 read_qual<-as.numeric(qual)
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144 threshold_upper<-as.numeric(thrup)
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145 threshold_lower<-as.numeric(thrlow)
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146 allele_ratio<-allr
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147 incl_complex<-complex
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148 loess_span<-as.numeric(lsp)
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149 plot_color<-pcol
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150 loess_color<-lcol
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151 xaxis_standard<-xstand
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152 bin_size<-as.numeric(bsize)
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153 bfreq_norm<-bnorm
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154 # exclusion_list<-exclf
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155 excl_threshold<-as.numeric(exclthr)
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156 excl_loess_color<-exclcol
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157 vcfoutput_filename<-outn
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158 vcfparsed_filename<-parn
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159 pdf_filename<-pdfn
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160
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161 #transparency for selected colour (to see plot points underneath)
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162 plot_color<-rgb(c(col2rgb(plot_color)[1]),c(col2rgb(plot_color)[2]),c(col2rgb(plot)[3]),max=255,alpha=150)
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163 loess_color<-rgb(c(col2rgb(loess_color)[1]),c(col2rgb(loess_color)[2]),c(col2rgb(loess_color)[3]),max=255,alpha=150)
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164 excl_loess_color<-rgb(c(col2rgb(excl_loess_color)[1]),c(col2rgb(excl_loess_color)[2]),c(col2rgb(excl_loess_color)[3]),max=255,alpha=150)
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165
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166 ###FIXED PARAMETERS
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167 #linkage scatter plot yaxis max value=1
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168 sp_yaxis<-1
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169 #chromosome intervals in Mb rather than custom
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170 interval_unit<-1000000
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171
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172
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173 ######################
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174 ###READ IN VCF FILE
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175 #extract column names
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176 vcf_readin<-readLines(filename)
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177 #find header line, i.e. last line to begin with #
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178 for(l in 1:length(vcf_readin)){
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179 vcf_readinl<-vcf_readin[l]
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180 if(substr(vcf_readinl,1,1)=="#"){next}
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181 else if(substr(vcf_readinl,1,1)!="#"){rowline<-l-1;break}
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182 }
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183 vcf_header<-vcf_readin[rowline]
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184 #e.g. CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\tFORMAT\trgSM"
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185 vcf_header<-gsub("#","",vcf_header)
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186 vcf_colnames<-unlist(strsplit(vcf_header,"\t"))
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187
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188 #extract data (hashed vcf header skipped with read.table)
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189 vcf_rtable<-read.table(filename,sep="\t",stringsAsFactors=FALSE)
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190 names(vcf_rtable)<-vcf_colnames
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191
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192 ######################
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193 ###PREPARE DATA
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194
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195 vcfinfo_dat<-NULL
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196 vcfinfo_pdat<-NULL
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197 multiallele_counter<-0
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198 diviserror_counter<-0
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199 for(i in c(1:nrow(vcf_rtable))){
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200 vcf_line<-vcf_rtable[i,]
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201 #to speed up runtime- quality filter here
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202 if(vcf_line$QUAL>=read_qual){
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203 #remove chrom or chr prefix from chromosome value
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204 if(grepl("chrom",vcf_line$CHROM,ignore.case=TRUE)==TRUE){
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205 vcf_line$CHROM<-gsub("chrom","",vcf_line$CHROM,ignore.case=TRUE)
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206 }else if(grepl("chr",vcf_line$CHROM,ignore.case=TRUE)==TRUE){
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207 vcf_line$CHROM<-gsub("chr","",vcf_line$CHROM,ignore.case=TRUE)
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208 }
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209 #PARSE INFO
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210 vcfinfo_split<-strsplit(vcf_line$INFO,split=";")
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211 vcfinfo_coln<-gsub("=.*","",unlist(vcfinfo_split))
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212 vcfinfo_cold<-gsub(".*=","",unlist(vcfinfo_split))
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213 vcfinfo_ldat<-data.frame(t(vcfinfo_cold),stringsAsFactors=FALSE)
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214 names(vcfinfo_ldat)<-vcfinfo_coln
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215
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216 #skip if commas in values to avoid returning errors
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217 if(grepl(",",vcfinfo_ldat$AO)==TRUE){
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218 multiallele_counter<-multiallele_counter+1
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219 next
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220 }
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221 #skip divide by zero errors (under "ratio" setting for ratio calculation)
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222 if(as.numeric(vcfinfo_ldat$AO)+as.numeric(vcfinfo_ldat$RO)=="0"){
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223 diviserror_counter<-diviserror_counter+1
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224 next
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225 }
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226
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227 #specific accounting for nonstandard categories
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228 #LOF columns only present for loss-of-function variants + assign NA values to all other variants
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229 if(("LOF" %in% names(vcfinfo_ldat))==TRUE){
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230 LOF<-vcfinfo_ldat$LOF
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231 vcfinfo_ldat<-vcfinfo_ldat[,!names(vcfinfo_ldat) %in% "LOF"]
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232 vcfinfo_ldat<-cbind(vcfinfo_ldat,LOF)
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233 }else{
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234 LOF<-"NA"
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235 vcfinfo_ldat<-cbind(vcfinfo_ldat,LOF)
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236 }
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237 #NMD columns only present for nonsense-mediated-decay variants + assign NA values to all other variants
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238 if(("NMD" %in% names(vcfinfo_ldat))==TRUE){
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239 NMD<-vcfinfo_ldat$NMD
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240 vcfinfo_ldat<-vcfinfo_ldat[,!names(vcfinfo_ldat) %in% "NMD"]
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241 vcfinfo_ldat<-cbind(vcfinfo_ldat,NMD)
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242 }else{
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243 NMD<-"NA"
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244 vcfinfo_ldat<-cbind(vcfinfo_ldat,NMD)
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245 }
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246
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247 #general accounting for nonstandard categories
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248
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249
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250 #PARSE ANNOTATION
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251 ann_rparsed<-unlist(strsplit(vcfinfo_ldat$ANN[1],split="\\|"))[1:20]
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252 ann_rparsed[ann_rparsed==""]<-"novalue"
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253 ann_parsed<-data.frame(t(ann_rparsed),stringsAsFactors=FALSE)
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254 names(ann_parsed)<-paste("ANN",c(1:dim(ann_parsed)[2]),sep="")
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255 #remove duplicate redundant INFO column (fully parsed)
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256 vcf_line<-vcf_line[,names(vcf_line)!="INFO"]
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257
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258 #dataset keeping unparsed annotation (full)
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259 vcfinfo_pldat<-cbind(vcf_line,vcfinfo_ldat)
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260 vcfinfo_pdat<-rbind(vcfinfo_pdat,vcfinfo_pldat)
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261
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262 #dataset keeping parsed annotation (partial parsed-for relevant)
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263 vcfinfo_ldat<-vcfinfo_ldat[,names(vcfinfo_ldat)!="ANN"]
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264 #append copy of original data to parsed data
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265 vcfinfo_lldat<-cbind(vcf_line,vcfinfo_ldat,ann_parsed)
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266 vcfinfo_dat<-rbind(vcfinfo_dat,vcfinfo_lldat)
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267 }
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268 }
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269 print(paste("rows with multiple alleles skipped: ",multiallele_counter,sep=""))
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270 # print(paste("rows with AO+RO=0 (not multiple alleles) skipped: ",diviserror_counter,sep=""))
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271
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272 #ENSURE CORRECT DATATYPES
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273 #convert dataframe columns of factor type to character type
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274 vcfinfo_dat<-data.frame(lapply(vcfinfo_dat,as.character),stringsAsFactors=FALSE)
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275 #convert to numeric if column is numeric and not string
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276 for(n in c(1:dim(vcfinfo_dat)[2])){
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277 #suppress warnings when columns with strings encountered (not converted)
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278 suppressWarnings(
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279 colnum_index<-!is.na(as.numeric(vcfinfo_dat[,n]))
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280 )
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281 if(all(colnum_index)==TRUE){
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282 vcfinfo_dat[,n]<-as.numeric(vcfinfo_dat[,n])
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283 }
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284 }
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285
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286 ######################
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287 #RATIO CALCULATION
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288 #ratio calculation from AO and RO
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289 RATIO<-c(vcfinfo_dat$AO/(vcfinfo_dat$AO+vcfinfo_dat$RO))
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290 #add adj_AB for AB=0->AO=1 conversion
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291 adj_AB<-replace(vcfinfo_dat$AB,vcfinfo_dat$AB==0,1)
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292 vcfinfo_dat<-cbind(vcfinfo_dat,RATIO,adj_AB)
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293 vcfinfo_dat<-vcfinfo_dat[with(vcfinfo_dat,order(CHROM,POS)),]
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294
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295 #EXCLUDE COMPLEX VARIANTS
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296 if(incl_complex==FALSE){
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297 vcfinfo_dat<-subset(vcfinfo_dat,CIGAR=="1X")
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298 }
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299
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300 ######################
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301 #SUBTRACT VARIANTS FROM EXCLUSION LIST
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302 if(length(exclusion_list)>0){
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303 #keep copy of pre-subtraction data for later plotting
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304 vcfinfo_origdat<-vcfinfo_dat
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305
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306 #identifiers for exclusion list based on CHROM/POS/REF/ALT
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307 index1<-paste(vcfinfo_dat$CHROM,vcfinfo_dat$POS,sep="_")
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308 index2<-paste(vcfinfo_dat$CHROM,vcfinfo_dat$POS,vcfinfo_dat$REF,sep="_")
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309 index3<-paste(vcfinfo_dat$CHROM,vcfinfo_dat$POS,vcfinfo_dat$REF,vcfinfo_dat$ALT,sep="_")
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310 vcfinfo_dat<-cbind(vcfinfo_dat,index1,index2,index3)
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311
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312 print(paste("before: ",nrow(vcfinfo_dat),sep=""))
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313 #loop and subtract through exclusion lists (if multiple files)
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314 for(exclusion_ind in exclusion_list){
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315 exclin<-read.table(exclusion_ind,header=TRUE)
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316
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317 #THRESHOLD FILTER ON EXCLUSION LIST VARIANTS
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318 if(allele_ratio=="AB"){
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319 exclin<-subset(exclin,adj_AB>=excl_threshold)
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320 }
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321 if(allele_ratio=="ratio"){
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322 exclin<-subset(exclin,ratio>=excl_threshold)
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323 }
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324
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325 #identifiers for vcf data based on CHROM/POS/REF/ALT
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326 index1<-paste(exclin$CHROM,exclin$POS,sep="_")
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327 index2<-paste(exclin$CHROM,exclin$POS,exclin$REF,sep="_")
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328 index3<-paste(exclin$CHROM,exclin$POS,exclin$REF,exclin$ALT,sep="_")
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329 exclin<-cbind(exclin,index1,index2,index3)
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330 #exclude based on CHROM+POS+REF+ALT
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331 vcfinfo_dat<-subset(vcfinfo_dat,!(index3 %in% exclin$index3))
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332 }
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333 print(paste("after: ",nrow(vcfinfo_dat),sep=""))
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334 }
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335
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336 ######################
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337 #WRITE TO OUTPUT
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338 #select relevant columns 2 variant type; 4 gene; !5 wormbase ID; 8 type change; 10 nucleotide change; 11 amino acid change; 16 warning message
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339 vcfinfo_simp<-subset(vcfinfo_dat,select=c("CHROM","POS","QUAL","DP","REF","ALT","AB","AO","RO","RATIO","adj_AB","ANN2","ANN4","ANN8","ANN10","ANN11","ANN16"))
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340 names(vcfinfo_simp)<-c("CHROM","POS","QUAL","DP","REF","ALT","AB","AO","RO","RATIO","adj_AB","VARTYPE","GENE","TYPE","NTCHANGE","PRCHANGE","WARNINGS")
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341 vcfsimp_dat<-vcfinfo_simp[with(vcfinfo_simp,order(CHROM,POS)),]
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342
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343 #write table with quality filtered variants for VDM plotting and relevant columns
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344 try(
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345 write.table(vcfsimp_dat,vcfoutput_filename,sep="\t",quote=FALSE,row.names=FALSE)
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346 ,silent=TRUE)
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347 #write table with all unfiltered variants and all columns including parsed INFO
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348 try(
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349 write.table(vcfinfo_pdat,vcfparsed_filename,sep="\t",quote=FALSE,row.names=FALSE)
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350 ,silent=TRUE)
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351
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352
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353 ######################
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354 ###CHROMOSOME (INTERVAL) ARRANGEMENT
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355 #define chromosome and chromosome size in Mb
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356 if(interval_type == 'C.elegans'){
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357 chrom_n<-c('I','II','III','IV','V','X')
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358 chrom_mb<-c(16,16,14,18,21,18)
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359 interval_frame<-data.frame(chrom_n,chrom_mb)
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360 } else if(interval_type == 'Zebrafish'){
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361 chrom_n<-c('1','2','3','4','5','6','7','8','9','10','11','12','13','14','15','16','17','18','19','20','21','22','23','24','25')
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362 chrom_mb<-c(61,61,64,63,76,60,78,57,59,47,47,51,55,54,48,59,54,50,51,56,45,43,47,44,39)
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363 interval_frame<-data.frame(chrom_n,chrom_mb)
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364 } else if(interval_type == 'Brachypodium'){
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365 chrom_n<-c('1','2','3','4','5')
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366 chrom_mb<-c(75,60,60,50,30)
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367 interval_frame<-data.frame(chrom_n,chrom_mb)
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368 } else if(interval_type == 'Arabidopsis'){
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369 chrom_n<-c('1','2','3','4','5')
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370 chrom_mb<-c(31, 20,24,19,27 )
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371 interval_frame<-data.frame(chrom_n,chrom_mb)
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372 } else{
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373 #user interval file- no headers, with chromosome in column 1 (format CHR# or CHROM#) and size in Mb (rounded up) in column 2
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374 user_interval_type<-read.table(user_interval_file)
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375 if(grepl("chrom",user_interval_type[1,1],ignore.case=TRUE)==TRUE){
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376 user_interval_type[,1]<-gsub("chrom","",user_interval_type[,1],ignore.case=TRUE)
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377 }else if(grep("chr",user_interval_type[1,1],ignore.case=TRUE)==TRUE){
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378 user_interval_type[,1]<-gsub("chr","",user_interval_type[,1],ignore.case=TRUE)
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379 }
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380 chrom_n<-user_interval_type[,1]
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381 chrom_mb<-user_interval_type[,2]
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382 interval_frame<-data.frame(chrom_n,chrom_mb)
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383 }
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384 names(interval_frame)<-c("CHROM","INTERVAL")
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385
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386
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387 ######################
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388 ###PLOTTING
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389 #VDM SCATTER PLOT
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390 #save to pdf
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391 pdf(file=pdf_filename,width=9,height=8)
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392 #par(mfrow=c(2,3))
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393 for(chromind in interval_frame$CHROM){
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394 #subset by data by chromosome for plotting
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395 intervalind<-interval_frame$INTERVAL[interval_frame$CHROM==chromind]
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396 chr_dat<-subset(vcfsimp_dat,CHROM==chromind,silent=TRUE)
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397
|
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398 #same subsetting by chromosome for pre-subtraction data
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|
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399 if(length(exclusion_list)>0){
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400 chr_origdat<-subset(vcfinfo_origdat,CHROM==chromind,silent=TRUE)
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|
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401 }
|
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402
|
|
|
403 #define x-axis upper limit
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|
|
404 if(xaxis_standard==TRUE){
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|
|
405 #for standardized x-axis (max x-axis chromosome length)
|
|
|
406 scupper_xaxis<-max(interval_frame$INTERVAL)
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|
|
407 scupper_xval<-scupper_xaxis*interval_unit
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|
|
408 } else if(xaxis_standard==FALSE){
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409 scupper_xaxis<-intervalind
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|
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410 scupper_xval<-intervalind*interval_unit
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|
|
411 }
|
|
|
412
|
|
|
413 if(allele_ratio=="AB"){
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414 plot(chr_dat$POS,chr_dat$adj_AB,cex=0.60,xlim=c(0,scupper_xval),ylim=c(0,sp_yaxis),main=paste("Chr",chromind," Variant Discovery Mapping",sep=""),xlab="Position along Chromosome (in Mb)",ylab='Ratio of Variant Reads/Total Reads [AB]',pch=10, col=plot_color,xaxt='n')
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|
|
415 try(lines(loess.smooth(chr_dat$POS,chr_dat$adj_AB,span=loess_span),lwd=5,col=loess_color))
|
|
|
416 #plot loess curve for data without subtraction of exclusion variants
|
|
|
417 if(length(exclusion_list)>0){
|
|
|
418 try(lines(loess.smooth(chr_origdat$POS,chr_origdat$adj_AB,span=loess_span),lwd=5,col=excl_loess_color))
|
|
|
419 }
|
|
|
420
|
|
|
421 axis(1,at=seq(0,scupper_xval,by=interval_unit),labels=c(0:scupper_xaxis))
|
|
|
422 abline(h=seq(0,sp_yaxis,by=0.1),v=c(1:scupper_xaxis)*interval_unit,col="gray")
|
|
|
423 } else if(allele_ratio=="ratio"){
|
|
|
424 plot(chr_dat$POS,chr_dat$RATIO,cex=0.60,xlim=c(0,scupper_xval),ylim=c(0,sp_yaxis),main=paste("Chr",chromind," Variant Discovery Mapping",sep=""),xlab="Position along Chromosome (in Mb)",ylab='Ratio of Variant Reads/Total Reads [ratio]',pch=10, col=plot,xaxt='n')
|
|
|
425 try(lines(loess.smooth(chr_dat$POS,chr_dat$RATIO,span=loess_span),lwd=5,col=loess_color))
|
|
|
426 #plot loess curve for data without subtraction of exclusion variants
|
|
|
427 if(length(exclusion_list)>0){
|
|
|
428 try(lines(loess.smooth(chr_origdat$POS,chr_origdat$adj_AB,span=loess_span),lwd=5,col=excl_loess_color))
|
|
|
429 }
|
|
|
430 axis(1,at=seq(0,scupper_xval,by=interval_unit),labels=c(0:scupper_xaxis))
|
|
|
431 abline(h=seq(0,sp_yaxis,by=0.1),v=c(1:scupper_xaxis)*interval_unit,col="gray")
|
|
|
432 }
|
|
|
433 }
|
|
|
434
|
|
|
435 ######################
|
|
|
436 #graph barplots
|
|
|
437 location_index<-NULL
|
|
|
438 meanSNP_dat<-NULL
|
|
|
439 # prepare table of counts and calculations
|
|
|
440 for(chromind in interval_frame$CHROM){
|
|
|
441 #for standardized x-axis
|
|
|
442 if(xaxis_standard==TRUE){
|
|
|
443 intervalind<-max(interval_frame$INTERVAL)*1000000/bin_size
|
|
|
444 } else if(xaxis_standard==FALSE){
|
|
|
445 intervalind<-interval_frame$INTERVAL[interval_frame$CHROM==chromind]*1000000/bin_size
|
|
|
446 }
|
|
|
447 #start intervals with **1 and end with **0
|
|
|
448 interval_begin<-c(((0:(intervalind-1))*bin_size)+1)
|
|
|
449 interval_end<-c((1:intervalind)*bin_size)
|
|
|
450
|
|
|
451 #define x-axis upper limit
|
|
|
452 if(xaxis_standard==TRUE){
|
|
|
453 upper_xaxis<-max(interval_frame$INTERVAL)
|
|
|
454 } else if(xaxis_standard==FALSE){
|
|
|
455 upper_xaxis<-interval_frame$INTERVAL[interval_frame$CHROM==chromind]
|
|
|
456 }
|
|
|
457 #prepare columns
|
|
|
458 snp_counter<-0
|
|
|
459 purealt_counter<-0
|
|
|
460 pureref_counter<-0
|
|
|
461 het_counter<-0
|
|
|
462 chr_mean<-0
|
|
|
463 normed_freq<-0
|
|
|
464 ratio<-0
|
|
|
465
|
|
|
466 interval_index<-data.frame(chromind,interval_begin,interval_end,snp_counter,purealt_counter,pureref_counter,het_counter,chr_mean,normed_freq)
|
|
|
467 chr_dat<-subset(vcfinfo_dat,CHROM==chromind)
|
|
|
468 #ratio calculation
|
|
|
469 ratio<-chr_dat$AO/(chr_dat$AO+chr_dat$RO)
|
|
|
470
|
|
|
471 #if counter based on adj_AB or ratio
|
|
|
472 if(allele_ratio=="ratio"){
|
|
|
473 chr_purealtdat<-subset(chr_dat,ratio>=threshold_upper)#;chr_purealtdat
|
|
|
474 chr_purerefdat<-subset(chr_dat,ratio<=threshold_lower)#;chr_purerefdat
|
|
|
475 chr_hetdat<-subset(chr_dat,ratio>threshold_lower & ratio<threshold_upper)#;chr_hetdat
|
|
|
476 } else if(allele_ratio=="AB"){
|
|
|
477 chr_purealtdat<-subset(chr_dat,adj_AB>=threshold_upper)#;chr_purealtdat
|
|
|
478 chr_purerefdat<-subset(chr_dat,adj_AB<=threshold_lower)#;chr_purerefdat
|
|
|
479 chr_hetdat<-subset(chr_dat,adj_AB>threshold_lower & adj_AB<threshold_upper)#;chr_hetdat
|
|
|
480 }
|
|
|
481 #if chromosome with data, count number of snps within each bin (positions rounded up to nearest bin), else skip to next chromosome
|
|
|
482 if(dim(chr_dat)[1]>0){
|
|
|
483 for(i in 1:dim(chr_dat)[1]){
|
|
|
484 chr_datind<-chr_dat[i,]
|
|
|
485 #round up to nearest bin-size interval
|
|
|
486 chr_datind_upper<-ceiling(chr_datind$POS/bin_size)*bin_size
|
|
|
487 interval_coln<-NULL;interval_rown<-NULL
|
|
|
488 #identify row and and counter column to increment
|
|
|
489 interval_coln<-which(names(interval_index)=="snp_counter")
|
|
|
490 interval_rown<-match(chr_datind_upper,interval_index$interval_end)
|
|
|
491 interval_index[interval_rown,interval_coln]<-c(interval_index$snp_counter[interval_rown]+1)
|
|
|
492 }
|
|
|
493 }else{
|
|
|
494 next
|
|
|
495 }
|
|
|
496 ##if chromosome with pure AO, count number of snps with each bin (positions rounded up to nearest bin)
|
|
|
497 if(dim(chr_purealtdat)[1]>0){
|
|
|
498 for(i in 1:dim(chr_purealtdat)[1]){
|
|
|
499 chr_purealtind<-chr_purealtdat[i,]
|
|
|
500 chr_purealtind_upper<-ceiling(chr_purealtind$POS/bin_size)*bin_size
|
|
|
501 interval_coln<-NULL;interval_rown<-NULL
|
|
|
502 interval_coln<-which(names(interval_index)=="purealt_counter")
|
|
|
503 interval_rown<-match(chr_purealtind_upper,interval_index$interval_end)
|
|
|
504 interval_index[interval_rown,interval_coln]<-c(interval_index$purealt_counter[interval_rown]+1)
|
|
|
505 }
|
|
|
506 }
|
|
|
507 #if chromosome with pure RO, count number of snps with each bin (positions rounded up to nearest bin)
|
|
|
508 if(dim(chr_purerefdat)[1]>0){
|
|
|
509 for(i in 1:dim(chr_purerefdat)[1]){
|
|
|
510 chr_purerefind<-chr_purerefdat[i,]
|
|
|
511 chr_purerefind_upper<-ceiling(chr_purerefind$POS/bin_size)*bin_size
|
|
|
512 interval_coln<-NULL;interval_rown<-NULL
|
|
|
513 interval_coln<-which(names(interval_index)=="pureref_counter")
|
|
|
514 interval_rown<-match(chr_purerefind_upper,interval_index$interval_end)
|
|
|
515 interval_index[interval_rown,interval_coln]<-c(interval_index$pureref_counter[interval_rown]+1)
|
|
|
516 }
|
|
|
517 }
|
|
|
518 #if chromosome with hets, count number of snps with each bin (positions rounded up to nearest bin)
|
|
|
519 if(dim(chr_hetdat)[1]>0){
|
|
|
520 for(i in 1:dim(chr_hetdat)[1]){
|
|
|
521 chr_hetind<-chr_hetdat[i,]
|
|
|
522 chr_hetind_upper<-ceiling(chr_hetind$POS/bin_size)*bin_size
|
|
|
523 interval_coln<-NULL;interval_rown<-NULL
|
|
|
524 interval_coln<-which(names(interval_index)=="het_counter")
|
|
|
525 interval_rown<-match(chr_hetind_upper,interval_index$interval_end)
|
|
|
526 interval_index[interval_rown,interval_coln]<-c(interval_index$het_counter[interval_rown]+1)
|
|
|
527 }
|
|
|
528 }
|
|
|
529 #irrespective of standardized x-axis, mean should be calculated from actual interval range of chromosome
|
|
|
530 chr_mean<-sum(interval_index$purealt_counter)/(interval_frame$INTERVAL[interval_frame$CHROM==chromind]*1000000/bin_size)
|
|
|
531 interval_index$chr_mean<-chr_mean
|
|
|
532 meanSNP_dat<-rbind(meanSNP_dat,data.frame(chromind,chr_mean))
|
|
|
533 #normalization treatment for if SNPs are AO=0, AO=total SNPs, or AO and RO in bin
|
|
|
534 for(i in 1:dim(interval_index)[1]){
|
|
|
535 chr_intind<-interval_index[i,]
|
|
|
536 #hom definition based on specified upper and lower thresholds
|
|
|
537 if(chr_intind$purealt_counter<=threshold_lower){
|
|
|
538 interval_coln<-NULL
|
|
|
539 interval_coln<-which(names(interval_index)=="normed_freq")
|
|
|
540 interval_index[i,interval_coln]=0
|
|
|
541 } else if (chr_intind$purealt_counter==chr_intind$snp_counter){
|
|
|
542 interval_coln<-NULL
|
|
|
543 interval_coln<-which(names(interval_index)=="normed_freq")
|
|
|
544 interval_index[i,interval_coln]=(chr_intind$purealt_counter)^2/chr_mean
|
|
|
545 } else {
|
|
|
546 interval_coln<-NULL
|
|
|
547 interval_coln<-which(names(interval_index)=="normed_freq")
|
|
|
548 interval_index[i,interval_coln]=chr_mean*(chr_intind$purealt_counter)^2/(chr_intind$snp_counter-chr_intind$purealt_counter)
|
|
|
549 }
|
|
|
550 }
|
|
|
551 location_index<-rbind(location_index,interval_index)
|
|
|
552 }
|
|
|
553
|
|
|
554 for(chromind in interval_frame$CHROM){
|
|
|
555 interval_index<-location_index[location_index$chromind==chromind,]
|
|
|
556 #assign 0 values to avoid empty datatable error
|
|
|
557 if(dim(interval_index)[1]==0){
|
|
|
558 interval_index[1,]<-rep(0,dim(interval_index)[2])
|
|
|
559 }
|
|
|
560 }
|
|
|
561 #set up x_axis
|
|
|
562 if(xaxis_standard==TRUE){
|
|
|
563 #for standardized x-axis (max x-axis chromosome length)
|
|
|
564 bpupper_xaxis<-max(interval_frame$INTERVAL)
|
|
|
565 bpupper_xval<-bpupper_xaxis*interval_unit
|
|
|
566 } else if(xaxis_standard==FALSE){
|
|
|
567 bpupper_xaxis<-intervalind
|
|
|
568 bpupper_xval<-intervalind*interval_unit
|
|
|
569 }
|
|
|
570 #set up y_axis range for barplots
|
|
|
571 if(bfreq_norm==TRUE){
|
|
|
572 bp_yaxis<-5*ceiling(max(location_index$normed_freq)/5)
|
|
|
573 #assign non-0 value to yaxis to avoid error
|
|
|
574 if(bp_yaxis==0){
|
|
|
575 bp_yaxis<-10
|
|
|
576 }
|
|
|
577 # }
|
|
|
578 if(xaxis_standard==TRUE){
|
|
|
579 bplot<-barplot(interval_index$normed_freq,space=0,ylim=c(0,bp_yaxis),main=paste("Chr",chromind," Variant Only",sep=""),xlab="Position along Chromosome (in Mb)",ylab='Normalised Frequency')
|
|
|
580 }else if(xaxis_standard==FALSE){
|
|
|
581 bplot<-barplot(interval_index$normed_freq,space=0,xlim=c(0,bpupper_xaxis),ylim=c(0,bp_yaxis),main=paste("Chr",chromind," Variant Only",sep=""),xlab="Position along Chromosome (in Mb)",ylab='Normalised Frequency')
|
|
|
582 }
|
|
|
583 }else if(bfreq_norm==FALSE){
|
|
|
584 bp_yaxis<-5*ceiling(max(location_index$purealt_counter)/5)
|
|
|
585 #assign non-0 value to yaxis to avoid error
|
|
|
586 if(bp_yaxis==0){
|
|
|
587 bp_yaxis<-10
|
|
|
588 }
|
|
|
589 # }
|
|
|
590 if(xaxis_standard==TRUE){
|
|
|
591 bplot<-barplot(interval_index$purealt_counter,space=0,ylim=c(0,bp_yaxis),main=paste("Chr",chromind," Variant Only",sep=""),xlab="Position along Chromosome (in Mb)",ylab='Frequency')
|
|
|
592 }else if(xaxis_standard==FALSE){
|
|
|
593 bplot<-barplot(interval_index$purealt_counter,space=0,xlim=c(0,bpupper_xaxis),ylim=c(0,bp_yaxis),main=paste("Chr",chromind," Variant Only",sep=""),xlab="Position along Chromosome (in Mb)",ylab='Frequency')
|
|
|
594 }
|
|
|
595
|
|
|
596 bp_xaxis1<-as.numeric(bplot)
|
|
|
597 bp_xaxis2<-c(bp_xaxis1,tail(bp_xaxis1,1)+bp_xaxis1[2]-bp_xaxis1[1])
|
|
|
598 bp_xaxis<-bp_xaxis2-bp_xaxis1[1]
|
|
|
599
|
|
|
600 axis(1,at=bp_xaxis,labels=seq(0,bpupper_xaxis,by=c(bin_size/1000000)))
|
|
|
601 }
|
|
|
602 dev.off()
|
|
|
603
|
|
|
604
|
