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0
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1 #options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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2
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3 args <- commandArgs(trailingOnly = TRUE)
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4
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5 inFile = args[1]
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6 outFile = args[2]
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7 outDir = args[3]
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8 clonalType = args[4]
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3
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9 species = args[5]
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10 locus = args[6]
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11 selection = args[7]
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0
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12
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13 if (!("gridExtra" %in% rownames(installed.packages()))) {
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14 install.packages("gridExtra", repos="http://cran.xl-mirror.nl/")
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15 }
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16 library(gridExtra)
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17 if (!("ggplot2" %in% rownames(installed.packages()))) {
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18 install.packages("ggplot2", repos="http://cran.xl-mirror.nl/")
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19 }
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20 require(ggplot2)
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21 if (!("plyr" %in% rownames(installed.packages()))) {
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22 install.packages("plyr", repos="http://cran.xl-mirror.nl/")
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23 }
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24 require(plyr)
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25
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26 if (!("data.table" %in% rownames(installed.packages()))) {
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27 install.packages("data.table", repos="http://cran.xl-mirror.nl/")
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28 }
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29 library(data.table)
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30
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2
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31 if (!("reshape2" %in% rownames(installed.packages()))) {
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32 install.packages("reshape2", repos="http://cran.xl-mirror.nl/")
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33 }
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34 library(reshape2)
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35
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0
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36
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37 test = read.table(inFile, sep="\t", header=TRUE, fill=T, comment.char="")
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38
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39 test = test[test$Sample != "",]
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40
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2
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41
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42
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0
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43 test$Top.V.Gene = gsub("[*]([0-9]+)", "", test$Top.V.Gene)
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44 test$Top.D.Gene = gsub("[*]([0-9]+)", "", test$Top.D.Gene)
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45 test$Top.J.Gene = gsub("[*]([0-9]+)", "", test$Top.J.Gene)
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46
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47 #test$VDJCDR3 = do.call(paste, c(test[c("Top.V.Gene", "Top.D.Gene", "Top.J.Gene","CDR3.Seq.DNA")], sep = ":"))
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48 test$VDJCDR3 = do.call(paste, c(test[unlist(strsplit(clonalType, ","))], sep = ":"))
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49
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50 PROD = test[test$VDJ.Frame != "In-frame with stop codon" & test$VDJ.Frame != "Out-of-frame" & test$CDR3.Found.How != "NOT_FOUND" , ]
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51 if("Functionality" %in% colnames(test)) {
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52 PROD = test[test$Functionality == "productive" | test$Functionality == "productive (see comment)", ]
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53 }
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54
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55 NONPROD = test[test$VDJ.Frame == "In-frame with stop codon" | test$VDJ.Frame == "Out-of-frame" | test$CDR3.Found.How == "NOT_FOUND" , ]
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56
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57 #PRODF = PROD[ -1]
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58
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59 PRODF = PROD
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60
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61 #PRODF = unique(PRODF)
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2
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62 if(any(grepl(pattern="_", x=PRODF$ID))){
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0
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63
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2
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64 PRODF$freq = gsub("^[0-9]+_", "", PRODF$ID)
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65 PRODF$freq = gsub("_.*", "", PRODF$freq)
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66 PRODF$freq = as.numeric(PRODF$freq)
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67 } else {
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68 PRODF$freq = 1
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3
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69 if(selection == "unique"){
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70 PRODF = PRODF[!duplicated(PRODF$VDJCDR3), ]
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71 }
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2
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72 }
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73
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74 PRODFV = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Sample", "Top.V.Gene")])
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0
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75 PRODFV$Length = as.numeric(PRODFV$Length)
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76 Total = 0
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77 Total = ddply(PRODFV, .(Sample), function(x) data.frame(Total = sum(x$Length)))
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78 PRODFV = merge(PRODFV, Total, by.x='Sample', by.y='Sample', all.x=TRUE)
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79 PRODFV = ddply(PRODFV, c("Sample", "Top.V.Gene"), summarise, relFreq= (Length*100 / Total))
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80
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2
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81 PRODFD = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Sample", "Top.D.Gene")])
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0
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82 PRODFD$Length = as.numeric(PRODFD$Length)
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83 Total = 0
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84 Total = ddply(PRODFD, .(Sample), function(x) data.frame(Total = sum(x$Length)))
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85 PRODFD = merge(PRODFD, Total, by.x='Sample', by.y='Sample', all.x=TRUE)
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86 PRODFD = ddply(PRODFD, c("Sample", "Top.D.Gene"), summarise, relFreq= (Length*100 / Total))
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87
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2
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88 PRODFJ = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Sample", "Top.J.Gene")])
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0
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89 PRODFJ$Length = as.numeric(PRODFJ$Length)
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90 Total = 0
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91 Total = ddply(PRODFJ, .(Sample), function(x) data.frame(Total = sum(x$Length)))
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92 PRODFJ = merge(PRODFJ, Total, by.x='Sample', by.y='Sample', all.x=TRUE)
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93 PRODFJ = ddply(PRODFJ, c("Sample", "Top.J.Gene"), summarise, relFreq= (Length*100 / Total))
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94
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3
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95 V = c("v.name\tchr.orderV\n")
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96 D = c("v.name\tchr.orderD\n")
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97 J = c("v.name\tchr.orderJ\n")
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98
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99 if(species == "human"){
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100 if(locus == "trb"){
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101 V = c("v.name\tchr.orderV\nTRBV2\t1\nTRBV3-1\t2\nTRBV4-1\t3\nTRBV5-1\t4\nTRBV6-1\t5\nTRBV4-2\t6\nTRBV6-2\t7\nTRBV4-3\t8\nTRBV6-3\t9\nTRBV7-2\t10\nTRBV6-4\t11\nTRBV7-3\t12\nTRBV9\t13\nTRBV10-1\t14\nTRBV11-1\t15\nTRBV10-2\t16\nTRBV11-2\t17\nTRBV6-5\t18\nTRBV7-4\t19\nTRBV5-4\t20\nTRBV6-6\t21\nTRBV5-5\t22\nTRBV7-6\t23\nTRBV5-6\t24\nTRBV6-8\t25\nTRBV7-7\t26\nTRBV6-9\t27\nTRBV7-8\t28\nTRBV5-8\t29\nTRBV7-9\t30\nTRBV13\t31\nTRBV10-3\t32\nTRBV11-3\t33\nTRBV12-3\t34\nTRBV12-4\t35\nTRBV12-5\t36\nTRBV14\t37\nTRBV15\t38\nTRBV16\t39\nTRBV18\t40\nTRBV19\t41\nTRBV20-1\t42\nTRBV24-1\t43\nTRBV25-1\t44\nTRBV27\t45\nTRBV28\t46\nTRBV29-1\t47\nTRBV30\t48")
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102 D = c("v.name\tchr.orderD\nTRBD1\t1\nTRBD2\t2\n")
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103 J = c("v.name\tchr.orderJ\nTRBJ1-1\t1\nTRBJ1-2\t2\nTRBJ1-3\t3\nTRBJ1-4\t4\nTRBJ1-5\t5\nTRBJ1-6\t6\nTRBJ2-1\t7\nTRBJ2-2\t8\nTRBJ2-3\t9\nTRBJ2-4\t10\nTRBJ2-5\t11\nTRBJ2-6\t12\nTRBJ2-7\t13")
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104 } else if (locus == "tra"){
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105 V = c("v.name\tchr.orderVTRAV1-1\t1\nTRAV1-2\t2\nTRAV2\t3\nTRAV3\t4\nTRAV4\t5\nTRAV5\t6\nTRAV6\t7\nTRAV7\t8\nTRAV8-1\t9\nTRAV9-1\t10\nTRAV10\t11\nTRAV12-1\t12\nTRAV8-2\t13\nTRAV8-3\t14\nTRAV13-1\t15\nTRAV12-2\t16\nTRAV8-4\t17\nTRAV13-2\t18\nTRAV14/DV4\t19\nTRAV9-2\t20\nTRAV12-3\t21\nTRAV8-6\t22\nTRAV16\t23\nTRAV17\t24\nTRAV18\t25\nTRAV19\t26\nTRAV20\t27\nTRAV21\t28\nTRAV22\t29\nTRAV23/DV6\t30\nTRAV24\t31\nTRAV25\t32\nTRAV26-1\t33\nTRAV27\t34\nTRAV29/DV5\t35\nTRAV30\t36\nTRAV26-2\t37\nTRAV34\t38\nTRAV35\t39\nTRAV36/DV7\t40\nTRAV38-1\t41\nTRAV38-2/DV8\t42\nTRAV39\t43\nTRAV40\t44\nTRAV41\t45\n")
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106 D = c("v.name\tchr.orderD\n")
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107 J = c("v.name\tchr.orderJ\nTRAJ57\t1\nTRAJ56\t2\nTRAJ54\t3\nTRAJ53\t4\nTRAJ52\t5\nTRAJ50\t6\nTRAJ49\t7\nTRAJ48\t8\nTRAJ47\t9\nTRAJ46\t10\nTRAJ45\t11\nTRAJ44\t12\nTRAJ43\t13\nTRAJ42\t14\nTRAJ41\t15\nTRAJ40\t16\nTRAJ39\t17\nTRAJ38\t18\nTRAJ37\t19\nTRAJ36\t20\nTRAJ34\t21\nTRAJ33\t22\nTRAJ32\t23\nTRAJ31\t24\nTRAJ30\t25\nTRAJ29\t26\nTRAJ28\t27\nTRAJ27\t28\nTRAJ26\t29\nTRAJ24\t30\nTRAJ23\t31\nTRAJ22\t32\nTRAJ21\t33\nTRAJ20\t34\nTRAJ18\t35\nTRAJ17\t36\nTRAJ16\t37\nTRAJ15\t38\nTRAJ14\t39\nTRAJ13\t40\nTRAJ12\t41\nTRAJ11\t42\nTRAJ10\t43\nTRAJ9\t44\nTRAJ8\t45\nTRAJ7\t46\nTRAJ6\t47\nTRAJ5\t48\nTRAJ4\t49\nTRAJ3\t50")
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108 } else if (locus == "trg"){
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109 cat("human trg not yet implemented")
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110 } else if (locus == "trd"){
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111 cat("human trd not yet implemented")
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112 }
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113 } else if (species == "mouse"){
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114 if(locus == "trb"){
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115 cat("mouse trb not yet implemented")
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116 } else if (locus == "tra"){
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117 cat("mouse tra not yet implemented")
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118 } else if (locus == "trg"){
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119 cat("mouse trg not yet implemented")
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120 } else if (locus == "trd"){
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121 cat("mouse trd not yet implemented")
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122 }
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123 }
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124 useD = TRUE
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125 if(species == "human" && locus == "tra"){
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126 useD = FALSE
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127 cat("No D Genes in this species/locus")
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128 }
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129
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130
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0
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131 tcV = textConnection(V)
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132 Vchain = read.table(tcV, sep="\t", header=TRUE)
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133 PRODFV = merge(PRODFV, Vchain, by.x='Top.V.Gene', by.y='v.name', all.x=TRUE)
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134 close(tcV)
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135
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3
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136
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0
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137 tcD = textConnection(D)
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138 Dchain = read.table(tcD, sep="\t", header=TRUE)
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139 PRODFD = merge(PRODFD, Dchain, by.x='Top.D.Gene', by.y='v.name', all.x=TRUE)
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140 close(tcD)
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141
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142
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3
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143
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0
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144 tcJ = textConnection(J)
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145 Jchain = read.table(tcJ, sep="\t", header=TRUE)
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146 PRODFJ = merge(PRODFJ, Jchain, by.x='Top.J.Gene', by.y='v.name', all.x=TRUE)
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147 close(tcJ)
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148
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149 setwd(outDir)
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150
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2
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151 write.table(PRODF, "allUnique.csv", sep=",",quote=F,row.names=F,col.names=T)
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0
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152
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153 pV = ggplot(PRODFV)
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154 pV = pV + geom_bar( aes( x=factor(reorder(Top.V.Gene, chr.orderV)), y=relFreq, fill=Sample), stat='identity', position="dodge") + theme(axis.text.x = element_text(angle = 90, hjust = 1))
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155 pV = pV + xlab("Summary of V gene") + ylab("Frequency") + ggtitle("Relative frequency of V gene usage")
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2
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156 write.table(x=PRODFV, file="VFrequency.csv", sep=",",quote=F,row.names=F,col.names=T)
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0
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157
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158 png("VPlot.png",width = 1280, height = 720)
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159 pV
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160 dev.off();
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161
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162 pD = ggplot(PRODFD)
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163 pD = pD + geom_bar( aes( x=factor(reorder(Top.D.Gene, chr.orderD)), y=relFreq, fill=Sample), stat='identity', position="dodge") + theme(axis.text.x = element_text(angle = 90, hjust = 1))
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164 pD = pD + xlab("Summary of D gene") + ylab("Frequency") + ggtitle("Relative frequency of D gene usage")
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2
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165 write.table(x=PRODFD, file="DFrequency.csv", sep=",",quote=F,row.names=F,col.names=T)
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0
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166
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167 png("DPlot.png",width = 800, height = 600)
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168 pD
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169 dev.off();
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170
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171 pJ = ggplot(PRODFJ)
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172 pJ = pJ + geom_bar( aes( x=factor(reorder(Top.J.Gene, chr.orderJ)), y=relFreq, fill=Sample), stat='identity', position="dodge") + theme(axis.text.x = element_text(angle = 90, hjust = 1))
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173 pJ = pJ + xlab("Summary of J gene") + ylab("Frequency") + ggtitle("Relative frequency of J gene usage")
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2
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174 write.table(x=PRODFJ, file="JFrequency.csv", sep=",",quote=F,row.names=F,col.names=T)
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0
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175
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176 png("JPlot.png",width = 800, height = 600)
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177 pJ
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178 dev.off();
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179
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2
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180 VGenes = PRODF[,c("Sample", "Top.V.Gene", "freq")]
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181 VGenes$Top.V.Gene = gsub("-.*", "", VGenes$Top.V.Gene)
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182 VGenes = data.frame(data.table(VGenes)[, list(Count=sum(freq)), by=c("Sample", "Top.V.Gene")])
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183 TotalPerSample = data.frame(data.table(VGenes)[, list(total=sum(.SD$Count)), by=Sample])
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184 VGenes = merge(VGenes, TotalPerSample, by="Sample")
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185 VGenes$Frequency = VGenes$Count * 100 / VGenes$total
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186 VPlot = ggplot(VGenes)
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187 VPlot = VPlot + geom_bar(aes( x = Top.V.Gene, y = Frequency, fill = Sample), stat='identity', position='dodge' ) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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188 ggtitle("Distribution of V gene families") +
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189 ylab("Percentage of sequences")
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190 png("VFPlot.png")
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191 VPlot
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192 dev.off();
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193 write.table(x=VGenes, file="VFFrequency.csv", sep=",",quote=F,row.names=F,col.names=T)
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194
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195 DGenes = PRODF[,c("Sample", "Top.D.Gene", "freq")]
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196 DGenes$Top.D.Gene = gsub("-.*", "", DGenes$Top.D.Gene)
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197 DGenes = data.frame(data.table(DGenes)[, list(Count=sum(freq)), by=c("Sample", "Top.D.Gene")])
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198 TotalPerSample = data.frame(data.table(DGenes)[, list(total=sum(.SD$Count)), by=Sample])
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199 DGenes = merge(DGenes, TotalPerSample, by="Sample")
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200 DGenes$Frequency = DGenes$Count * 100 / DGenes$total
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201 DPlot = ggplot(DGenes)
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202 DPlot = DPlot + geom_bar(aes( x = Top.D.Gene, y = Frequency, fill = Sample), stat='identity', position='dodge' ) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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203 ggtitle("Distribution of D gene families") +
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204 ylab("Percentage of sequences")
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205 png("DFPlot.png")
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206 DPlot
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207 dev.off();
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208 write.table(x=DGenes, file="DFFrequency.csv", sep=",",quote=F,row.names=F,col.names=T)
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209
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210 JGenes = PRODF[,c("Sample", "Top.J.Gene", "freq")]
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211 JGenes$Top.J.Gene = gsub("-.*", "", JGenes$Top.J.Gene)
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212 JGenes = data.frame(data.table(JGenes)[, list(Count=sum(freq)), by=c("Sample", "Top.J.Gene")])
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213 TotalPerSample = data.frame(data.table(JGenes)[, list(total=sum(.SD$Count)), by=Sample])
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214 JGenes = merge(JGenes, TotalPerSample, by="Sample")
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215 JGenes$Frequency = JGenes$Count * 100 / JGenes$total
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216 JPlot = ggplot(JGenes)
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217 JPlot = JPlot + geom_bar(aes( x = Top.J.Gene, y = Frequency, fill = Sample), stat='identity', position='dodge' ) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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218 ggtitle("Distribution of J gene families") +
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219 ylab("Percentage of sequences")
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220 png("JFPlot.png")
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221 JPlot
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222 dev.off();
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223 write.table(x=JGenes, file="JFFrequency.csv", sep=",",quote=F,row.names=F,col.names=T)
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224
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225 CDR3Length = data.frame(data.table(PRODF)[, list(Count=sum(freq)), by=c("Sample", "CDR3.Length.DNA")])
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226 TotalPerSample = data.frame(data.table(CDR3Length)[, list(total=sum(.SD$Count)), by=Sample])
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227 CDR3Length = merge(CDR3Length, TotalPerSample, by="Sample")
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228 CDR3Length$Frequency = CDR3Length$Count * 100 / CDR3Length$total
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229 CDR3LengthPlot = ggplot(CDR3Length)
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230 CDR3LengthPlot = CDR3LengthPlot + geom_bar(aes( x = CDR3.Length.DNA, y = Frequency, fill = Sample), stat='identity', position='dodge' ) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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231 ggtitle("Length distribution of CDR3") +
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232 xlab("CDR3 Length") +
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233 ylab("Percentage of sequences")
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234 png("CDR3LengthPlot.png",width = 1280, height = 720)
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235 CDR3LengthPlot
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236 dev.off()
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237 write.table(x=CDR3Length, file="CDR3LengthPlot.csv", sep=",",quote=F,row.names=F,col.names=T)
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238
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0
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239 revVchain = Vchain
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240 revDchain = Dchain
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241 revVchain$chr.orderV = rev(revVchain$chr.orderV)
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242 revDchain$chr.orderD = rev(revDchain$chr.orderD)
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243
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3
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244
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0
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245 plotVD <- function(dat){
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246 if(length(dat[,1]) == 0){
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247 return()
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248 }
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249 img = ggplot() +
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250 geom_tile(data=dat, aes(x=factor(reorder(Top.D.Gene, chr.orderD)), y=factor(reorder(Top.V.Gene, chr.orderV)), fill=relLength)) +
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251 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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252 scale_fill_gradient(low="gold", high="blue", na.value="white") +
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253 ggtitle(paste(unique(dat$Sample), " (N=" , sum(dat$Length, na.rm=T) ,")", sep="")) +
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254 xlab("D genes") +
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255 ylab("V Genes")
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256
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257 png(paste("HeatmapVD_", unique(dat[3])[1,1] , ".png", sep=""), width=150+(15*length(Dchain$v.name)), height=100+(15*length(Vchain$v.name)))
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258 print(img)
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2
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259
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0
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260 dev.off()
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2
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261 write.table(x=acast(dat, Top.V.Gene~Top.D.Gene, value.var="Length"), file=paste("HeatmapVD_", unique(dat[3])[1,1], ".csv", sep=""), sep=",",quote=F,row.names=T,col.names=NA)
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0
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262 }
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263
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2
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264 VandDCount = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Top.V.Gene", "Top.D.Gene", "Sample")])
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0
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265
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266 VandDCount$l = log(VandDCount$Length)
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267 maxVD = data.frame(data.table(VandDCount)[, list(max=max(l)), by=c("Sample")])
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268 VandDCount = merge(VandDCount, maxVD, by.x="Sample", by.y="Sample", all.x=T)
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269 VandDCount$relLength = VandDCount$l / VandDCount$max
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270
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271 cartegianProductVD = expand.grid(Top.V.Gene = Vchain$v.name, Top.D.Gene = Dchain$v.name, Sample = unique(test$Sample))
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272
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273 completeVD = merge(VandDCount, cartegianProductVD, all.y=TRUE)
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274 completeVD = merge(completeVD, revVchain, by.x="Top.V.Gene", by.y="v.name", all.x=TRUE)
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275 completeVD = merge(completeVD, Dchain, by.x="Top.D.Gene", by.y="v.name", all.x=TRUE)
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276 VDList = split(completeVD, f=completeVD[,"Sample"])
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277
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278 lapply(VDList, FUN=plotVD)
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279
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280 plotVJ <- function(dat){
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281 if(length(dat[,1]) == 0){
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282 return()
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283 }
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284 img = ggplot() +
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285 geom_tile(data=dat, aes(x=factor(reorder(Top.J.Gene, chr.orderJ)), y=factor(reorder(Top.V.Gene, chr.orderV)), fill=relLength)) +
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286 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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287 scale_fill_gradient(low="gold", high="blue", na.value="white") +
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288 ggtitle(paste(unique(dat$Sample), " (N=" , sum(dat$Length, na.rm=T) ,")", sep="")) +
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289 xlab("J genes") +
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290 ylab("V Genes")
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291
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292 png(paste("HeatmapVJ_", unique(dat[3])[1,1] , ".png", sep=""), width=150+(15*length(Jchain$v.name)), height=100+(15*length(Vchain$v.name)))
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293 print(img)
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294 dev.off()
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2
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295 write.table(x=acast(dat, Top.V.Gene~Top.J.Gene, value.var="Length"), file=paste("HeatmapVJ_", unique(dat[3])[1,1], ".csv", sep=""), sep=",",quote=F,row.names=T,col.names=NA)
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0
|
296 }
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297
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2
|
298 VandJCount = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Top.V.Gene", "Top.J.Gene", "Sample")])
|
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0
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299
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300 VandJCount$l = log(VandJCount$Length)
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301 maxVJ = data.frame(data.table(VandJCount)[, list(max=max(l)), by=c("Sample")])
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302 VandJCount = merge(VandJCount, maxVJ, by.x="Sample", by.y="Sample", all.x=T)
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303 VandJCount$relLength = VandJCount$l / VandJCount$max
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304
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|
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305 cartegianProductVJ = expand.grid(Top.V.Gene = Vchain$v.name, Top.J.Gene = Jchain$v.name, Sample = unique(test$Sample))
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306
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307 completeVJ = merge(VandJCount, cartegianProductVJ, all.y=TRUE)
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308 completeVJ = merge(completeVJ, revVchain, by.x="Top.V.Gene", by.y="v.name", all.x=TRUE)
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309 completeVJ = merge(completeVJ, Jchain, by.x="Top.J.Gene", by.y="v.name", all.x=TRUE)
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310 VJList = split(completeVJ, f=completeVJ[,"Sample"])
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311 lapply(VJList, FUN=plotVJ)
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312
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313 plotDJ <- function(dat){
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314 if(length(dat[,1]) == 0){
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315 return()
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316 }
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|
317 img = ggplot() +
|
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318 geom_tile(data=dat, aes(x=factor(reorder(Top.J.Gene, chr.orderJ)), y=factor(reorder(Top.D.Gene, chr.orderD)), fill=relLength)) +
|
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|
319 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
|
|
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320 scale_fill_gradient(low="gold", high="blue", na.value="white") +
|
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|
321 ggtitle(paste(unique(dat$Sample), " (N=" , sum(dat$Length, na.rm=T) ,")", sep="")) +
|
|
|
322 xlab("J genes") +
|
|
|
323 ylab("D Genes")
|
|
|
324
|
|
|
325 png(paste("HeatmapDJ_", unique(dat[3])[1,1] , ".png", sep=""), width=150+(15*length(Jchain$v.name)), height=100+(15*length(Dchain$v.name)))
|
|
|
326 print(img)
|
|
|
327 dev.off()
|
|
2
|
328 write.table(x=acast(dat, Top.D.Gene~Top.J.Gene, value.var="Length"), file=paste("HeatmapDJ_", unique(dat[3])[1,1], ".csv", sep=""), sep=",",quote=F,row.names=T,col.names=NA)
|
|
0
|
329 }
|
|
|
330
|
|
|
331 DandJCount = data.frame(data.table(PRODF)[, list(Length=.N), by=c("Top.D.Gene", "Top.J.Gene", "Sample")])
|
|
|
332
|
|
|
333 DandJCount$l = log(DandJCount$Length)
|
|
|
334 maxDJ = data.frame(data.table(DandJCount)[, list(max=max(l)), by=c("Sample")])
|
|
|
335 DandJCount = merge(DandJCount, maxDJ, by.x="Sample", by.y="Sample", all.x=T)
|
|
|
336 DandJCount$relLength = DandJCount$l / DandJCount$max
|
|
|
337
|
|
|
338 cartegianProductDJ = expand.grid(Top.D.Gene = Dchain$v.name, Top.J.Gene = Jchain$v.name, Sample = unique(test$Sample))
|
|
|
339
|
|
|
340 completeDJ = merge(DandJCount, cartegianProductDJ, all.y=TRUE)
|
|
|
341 completeDJ = merge(completeDJ, revDchain, by.x="Top.D.Gene", by.y="v.name", all.x=TRUE)
|
|
|
342 completeDJ = merge(completeDJ, Jchain, by.x="Top.J.Gene", by.y="v.name", all.x=TRUE)
|
|
|
343 DJList = split(completeDJ, f=completeDJ[,"Sample"])
|
|
|
344 lapply(DJList, FUN=plotDJ)
|
|
|
345
|
|
|
346 sampleFile <- file("samples.txt")
|
|
|
347 un = unique(test$Sample)
|
|
|
348 un = paste(un, sep="\n")
|
|
|
349 writeLines(un, sampleFile)
|
|
|
350 close(sampleFile)
|
|
|
351
|
|
|
352
|
|
|
353 if("Replicate" %in% colnames(test))
|
|
|
354 {
|
|
|
355 clonalityFrame = PROD
|
|
|
356 clonalityFrame$ReplicateConcat = do.call(paste, c(clonalityFrame[c("VDJCDR3", "Sample", "Replicate")], sep = ":"))
|
|
|
357 clonalityFrame = clonalityFrame[!duplicated(clonalityFrame$ReplicateConcat), ]
|
|
2
|
358 write.table(clonalityFrame, "clonalityComplete.csv", sep=",",quote=F,row.names=F,col.names=T)
|
|
0
|
359
|
|
|
360 ClonalitySampleReplicatePrint <- function(dat){
|
|
2
|
361 write.table(dat, paste("clonality_", unique(dat$Sample) , "_", unique(dat$Replicate), ".csv", sep=""), sep=",",quote=F,row.names=F,col.names=T)
|
|
0
|
362 }
|
|
|
363
|
|
|
364 clonalityFrameSplit = split(clonalityFrame, f=clonalityFrame[,c("Sample", "Replicate")])
|
|
2
|
365 #lapply(clonalityFrameSplit, FUN=ClonalitySampleReplicatePrint)
|
|
0
|
366
|
|
|
367 ClonalitySamplePrint <- function(dat){
|
|
2
|
368 write.table(dat, paste("clonality_", unique(dat$Sample) , ".csv", sep=""), sep=",",quote=F,row.names=F,col.names=T)
|
|
0
|
369 }
|
|
|
370
|
|
|
371 clonalityFrameSplit = split(clonalityFrame, f=clonalityFrame[,"Sample"])
|
|
2
|
372 #lapply(clonalityFrameSplit, FUN=ClonalitySamplePrint)
|
|
0
|
373
|
|
|
374 clonalFreq = data.frame(data.table(clonalityFrame)[, list(Type=.N), by=c("Sample", "VDJCDR3")])
|
|
|
375 clonalFreqCount = data.frame(data.table(clonalFreq)[, list(Count=.N), by=c("Sample", "Type")])
|
|
|
376 clonalFreqCount$realCount = clonalFreqCount$Type * clonalFreqCount$Count
|
|
|
377 clonalSum = data.frame(data.table(clonalFreqCount)[, list(Reads=sum(realCount)), by=c("Sample")])
|
|
|
378 clonalFreqCount = merge(clonalFreqCount, clonalSum, by.x="Sample", by.y="Sample")
|
|
|
379
|
|
|
380 ct = c('Type\tWeight\n2\t1\n3\t3\n4\t6\n5\t10\n6\t15')
|
|
|
381 tcct = textConnection(ct)
|
|
|
382 CT = read.table(tcct, sep="\t", header=TRUE)
|
|
|
383 close(tcct)
|
|
|
384 clonalFreqCount = merge(clonalFreqCount, CT, by.x="Type", by.y="Type", all.x=T)
|
|
|
385 clonalFreqCount$WeightedCount = clonalFreqCount$Count * clonalFreqCount$Weight
|
|
|
386
|
|
|
387 ReplicateReads = data.frame(data.table(clonalityFrame)[, list(Type=.N), by=c("Sample", "Replicate", "VDJCDR3")])
|
|
|
388 ReplicateReads = data.frame(data.table(ReplicateReads)[, list(Reads=.N), by=c("Sample", "Replicate")])
|
|
|
389 clonalFreqCount$Reads = as.numeric(clonalFreqCount$Reads)
|
|
|
390 ReplicateReads$squared = ReplicateReads$Reads * ReplicateReads$Reads
|
|
|
391
|
|
|
392 ReplicatePrint <- function(dat){
|
|
|
393 write.table(dat[-1], paste("ReplicateReads_", unique(dat[1])[1,1] , ".csv", sep=""), sep=",",quote=F,na="-",row.names=F,col.names=F)
|
|
|
394 }
|
|
|
395
|
|
|
396 ReplicateSplit = split(ReplicateReads, f=ReplicateReads[,"Sample"])
|
|
|
397 lapply(ReplicateSplit, FUN=ReplicatePrint)
|
|
|
398
|
|
|
399 ReplicateReads = data.frame(data.table(ReplicateReads)[, list(ReadsSum=sum(Reads), ReadsSquaredSum=sum(squared)), by=c("Sample")])
|
|
|
400 clonalFreqCount = merge(clonalFreqCount, ReplicateReads, by.x="Sample", by.y="Sample", all.x=T)
|
|
|
401
|
|
|
402
|
|
|
403 ReplicateSumPrint <- function(dat){
|
|
|
404 write.table(dat[-1], paste("ReplicateSumReads_", unique(dat[1])[1,1] , ".csv", sep=""), sep=",",quote=F,na="-",row.names=F,col.names=F)
|
|
|
405 }
|
|
|
406
|
|
|
407 ReplicateSumSplit = split(ReplicateReads, f=ReplicateReads[,"Sample"])
|
|
|
408 lapply(ReplicateSumSplit, FUN=ReplicateSumPrint)
|
|
|
409
|
|
|
410 clonalFreqCountSum = data.frame(data.table(clonalFreqCount)[, list(Numerator=sum(WeightedCount, na.rm=T)), by=c("Sample")])
|
|
|
411 clonalFreqCount = merge(clonalFreqCount, clonalFreqCountSum, by.x="Sample", by.y="Sample", all.x=T)
|
|
|
412 clonalFreqCount$ReadsSum = as.numeric(clonalFreqCount$ReadsSum) #prevent integer overflow
|
|
|
413 clonalFreqCount$Denominator = (((clonalFreqCount$ReadsSum * clonalFreqCount$ReadsSum) - clonalFreqCount$ReadsSquaredSum) / 2)
|
|
|
414 clonalFreqCount$Result = (clonalFreqCount$Numerator + 1) / (clonalFreqCount$Denominator + 1)
|
|
|
415
|
|
|
416 ClonalityScorePrint <- function(dat){
|
|
|
417 write.table(dat$Result, paste("ClonalityScore_", unique(dat[1])[1,1] , ".csv", sep=""), sep=",",quote=F,na="-",row.names=F,col.names=F)
|
|
|
418 }
|
|
|
419
|
|
|
420 clonalityScore = clonalFreqCount[c("Sample", "Result")]
|
|
|
421 clonalityScore = unique(clonalityScore)
|
|
|
422
|
|
|
423 clonalityScoreSplit = split(clonalityScore, f=clonalityScore[,"Sample"])
|
|
|
424 lapply(clonalityScoreSplit, FUN=ClonalityScorePrint)
|
|
|
425
|
|
|
426 clonalityOverview = clonalFreqCount[c("Sample", "Type", "Count", "Weight", "WeightedCount")]
|
|
|
427
|
|
|
428
|
|
|
429
|
|
|
430 ClonalityOverviewPrint <- function(dat){
|
|
|
431 write.table(dat[-1], paste("ClonalityOverView_", unique(dat[1])[1,1] , ".csv", sep=""), sep=",",quote=F,na="-",row.names=F,col.names=F)
|
|
|
432 }
|
|
|
433
|
|
|
434 clonalityOverviewSplit = split(clonalityOverview, f=clonalityOverview$Sample)
|
|
|
435 lapply(clonalityOverviewSplit, FUN=ClonalityOverviewPrint)
|
|
|
436 }
|
|
|
437
|
|
|
438 if("Functionality" %in% colnames(test))
|
|
|
439 {
|
|
|
440 newData = data.frame(data.table(PROD)[,list(unique=.N,
|
|
|
441 VH.DEL=mean(X3V.REGION.trimmed.nt.nb),
|
|
|
442 P1=mean(P3V.nt.nb),
|
|
|
443 N1=mean(N1.REGION.nt.nb),
|
|
|
444 P2=mean(P5D.nt.nb),
|
|
|
445 DEL.DH=mean(X5D.REGION.trimmed.nt.nb),
|
|
|
446 DH.DEL=mean(X3D.REGION.trimmed.nt.nb),
|
|
|
447 P3=mean(P3D.nt.nb),
|
|
|
448 N2=mean(N2.REGION.nt.nb),
|
|
|
449 P4=mean(P5J.nt.nb),
|
|
|
450 DEL.JH=mean(X5J.REGION.trimmed.nt.nb),
|
|
|
451 Total.Del=( mean(X3V.REGION.trimmed.nt.nb) +
|
|
|
452 mean(X5D.REGION.trimmed.nt.nb) +
|
|
|
453 mean(X3D.REGION.trimmed.nt.nb) +
|
|
|
454 mean(X5J.REGION.trimmed.nt.nb)),
|
|
|
455
|
|
|
456 Total.N=( mean(N1.REGION.nt.nb) +
|
|
|
457 mean(N2.REGION.nt.nb)),
|
|
|
458
|
|
|
459 Total.P=( mean(P3V.nt.nb) +
|
|
|
460 mean(P5D.nt.nb) +
|
|
|
461 mean(P3D.nt.nb) +
|
|
|
462 mean(P5J.nt.nb))),
|
|
|
463 by=c("Sample")])
|
|
|
464 write.table(newData, "junctionAnalysis.csv" , sep=",",quote=F,na="-",row.names=F,col.names=F)
|
|
|
465 }
|
