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1 library(reshape2)
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2
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3 args <- commandArgs(trailingOnly = TRUE)
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4
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5 gene.matches = args[1]
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6 sequence.file = args[2]
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7 merged.file = args[3]
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8 outputdir = args[4]
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9 gene.classes = unlist(strsplit(args[5], ","))
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10 hotspot.analysis.sum.file = args[6]
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11 NToverview.file = paste(outputdir, "ntoverview.txt", sep="/")
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12 NTsum.file = paste(outputdir, "ntsum.txt", sep="/")
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13 main.html = "index.html"
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14
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15 setwd(outputdir)
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16
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17 genes = read.table(gene.matches, header=T, sep="\t", fill=T)
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18 sequences = read.table(sequence.file, header=T, sep="\t", fill=T, stringsAsFactors=F, quote="")
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19 merged = read.table(merged.file, header=T, sep="\t", fill=T, stringsAsFactors=F, quote="")
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20 hotspot.analysis.sum = read.table(hotspot.analysis.sum.file, header=F, sep=",", fill=T, stringsAsFactors=F, quote="")
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21
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22 dat = merge(sequences, genes, by="Sequence.ID")
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23
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24 dat = dat[dat$Sequence.ID %in% merged$Sequence.ID,]
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25
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26 dat$seq_conc = paste(dat$CDR1.IMGT, dat$FR2.IMGT, dat$CDR2.IMGT, dat$FR3.IMGT, dat$CDR3.IMGT)
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27 #dat$seq_conc = paste(dat$CDR1.IMGT, dat$CDR2.IMGT, dat$CDR3.IMGT)
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28
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29 IDs = dat[,c("Sequence.ID", "seq_conc", "best_match", "Functionality")]
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30 IDs$best_match = as.character(IDs$best_match)
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31
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32 #dat = data.frame(data.table(dat)[, list(freq=.N), by=c("best_match", "seq_conc")])
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33
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34 dat = data.frame(table(dat$seq_conc, dat$Functionality))
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35
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36 #dat = dat[dat$Freq > 1,]
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37
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38 names(dat) = c("seq_conc", "Functionality", "Freq")
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39
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40 dat$seq_conc = factor(dat$seq_conc)
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41
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42 dat = dat[order(as.character(dat$seq_conc)),]
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43
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44 #writing html from R...
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45 td = function(val) { paste("<td>", val, "</td>", sep="") }
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46 tr = function(val) { capture.output(cat("<tr>", td(val), "</tr>", sep="")) }
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47 make.link = function(id, clss, val) { paste("<a href='", clss, "_", id, ".html'>", val, "</a>", sep="") }
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48 tbl = function(df) { res = "<table border='1'>"; for(i in 1:nrow(df)){ res = paste(res, tr(df[i,]), sep=""); }; res = paste(res, "</table>"); }
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49
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50 cat("<table border='1'>", file=main.html, append=F)
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51 cat("<caption>CDR1+FR2+CDR2+FR3+CDR3 sequences that show up more than once</caption>", file=main.html, append=T)
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52 cat("<tr><th>Sequence</th><th>Functionality</th><th>ca1</th><th>ca2</th><th>cg1</th><th>cg2</th><th>cg3</th><th>cg4</th><th>cm</th></tr>", file=main.html, append=T)
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53
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54 for(i in 1:nrow(dat)){
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55 ca1 = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "ca1",]
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56 ca2 = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "ca2",]
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57
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58 cg1 = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "cg1",]
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59 cg2 = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "cg2",]
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60 cg3 = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "cg3",]
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61 cg4 = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "cg4",]
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62
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63 cm = IDs[IDs$seq_conc == dat[i,c("seq_conc")] & IDs$best_match == "cm",]
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64
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65 classes = c(nrow(ca1), nrow(ca2), nrow(cg1), nrow(cg2), nrow(cg3), nrow(cg4), nrow(cm))
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66
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67 classes.sum = sum(classes)
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68
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69 if(classes.sum == 1){
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70 next
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71 }
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72
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73 id = as.numeric(dat[i,"seq_conc"])
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74
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75 functionality = dat[i,"Functionality"]
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76
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77 if(nrow(ca1) > 0){
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78 cat(tbl(ca1), file=paste("ca1_", id, ".html", sep=""))
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79 }
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80
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81 if(nrow(ca2) > 0){
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82 cat(tbl(ca2), file=paste("ca2_", id, ".html", sep=""))
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83 }
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84
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85 if(nrow(cg1) > 0){
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86 cat(tbl(cg1), file=paste("cg1_", id, ".html", sep=""))
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87 }
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88
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89 if(nrow(cg2) > 0){
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90 cat(tbl(cg2), file=paste("cg2_", id, ".html", sep=""))
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91 }
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92
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93 if(nrow(cg3) > 0){
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94 cat(tbl(cg3), file=paste("cg3_", id, ".html", sep=""))
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95 }
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96
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97 if(nrow(cg4) > 0){
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98 cat(tbl(cg4), file=paste("cg4_", id, ".html", sep=""))
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99 }
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100
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101 if(nrow(cm) > 0){
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102 cat(tbl(cm), file=paste("cm_", id, ".html", sep=""))
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103 }
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104
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105 ca1.html = make.link(id, "ca1", nrow(ca1))
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106 ca2.html = make.link(id, "ca2", nrow(ca2))
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107
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108 cg1.html = make.link(id, "cg1", nrow(cg1))
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109 cg2.html = make.link(id, "cg2", nrow(cg2))
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110 cg3.html = make.link(id, "cg3", nrow(cg3))
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111 cg4.html = make.link(id, "cg4", nrow(cg4))
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112
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113 cm.html = make.link(id, "cm", nrow(cm))
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114
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115 rw = c(as.character(dat[i,"seq_conc"]), as.character(functionality), ca1.html, ca2.html, cg1.html, cg2.html, cg3.html, cg4.html, cm.html)
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116
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117 cat(tr(rw), file=main.html, append=T)
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118 }
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119
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120 cat("</table>", file=main.html, append=T)
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121
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122
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123 #ACGT overview
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124
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125
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126
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127 NToverview = genes[,c("Sequence.ID", "best_match")]
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128 sequences$seq = paste(sequences$CDR1.IMGT, sequences$FR2.IMGT, sequences$CDR2.IMGT, sequences$FR3.IMGT, sep="_")
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129
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130 NToverview = merge(NToverview, sequences[,c("Sequence.ID", "seq")], by="Sequence.ID")
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131
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132 NToverview = NToverview[NToverview$Sequence.ID %in% merged$Sequence.ID,]
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133
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134 NToverview$A = nchar(gsub("[^Aa]", "", NToverview$seq))
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135 NToverview$C = nchar(gsub("[^Cc]", "", NToverview$seq))
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136 NToverview$G = nchar(gsub("[^Gg]", "", NToverview$seq))
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137 NToverview$T = nchar(gsub("[^Tt]", "", NToverview$seq))
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138
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139 #Nsum = data.frame(Sequence.ID="-", best_match="Sum", seq="-", A = sum(NToverview$A), C = sum(NToverview$C), G = sum(NToverview$G), T = sum(NToverview$T))
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140
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141 #NToverview = rbind(NToverview, NTsum)
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142
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143 NTresult = data.frame(nt=c("A", "C", "T", "G"))
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144
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145 for(clazz in gene.classes){
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146 NToverview.sub = NToverview[grepl(clazz, paste("^", NToverview$best_match, sep="")),]
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147 new.col.x = c(sum(NToverview.sub$A), sum(NToverview.sub$C), sum(NToverview.sub$T), sum(NToverview.sub$G))
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148 new.col.y = sum(new.col.x)
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149 new.col.z = round(new.col.x / new.col.y * 100, 2)
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150
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151 tmp = names(NTresult)
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152 NTresult = cbind(NTresult, data.frame(new.col.x, new.col.y, new.col.z))
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153 names(NTresult) = c(tmp, paste(clazz, c("x", "y", "z"), sep=""))
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154 }
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155
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156 new.col.x = c(sum(NToverview$A), sum(NToverview$C), sum(NToverview$T), sum(NToverview$G))
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157 new.col.y = sum(new.col.x)
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158 new.col.z = round(new.col.x / new.col.y * 100, 2)
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159
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160 tmp = names(NTresult)
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161 NTresult = cbind(NTresult, data.frame(new.col.x, new.col.y, new.col.z))
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162 names(NTresult) = c(tmp, paste("all", c("x", "y", "z"), sep=""))
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163
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164 names(hotspot.analysis.sum) = names(NTresult)
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165
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166 hotspot.analysis.sum = rbind(hotspot.analysis.sum, NTresult)
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167
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168 print(hotspot.analysis.sum)
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169
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170 write.table(hotspot.analysis.sum, hotspot.analysis.sum.file, quote=F, sep=",", row.names=F, col.names=F, na="0")
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171
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172
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173 write.table(NToverview, NToverview.file, quote=F, sep="\t", row.names=F, col.names=T)
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