annotate report_clonality/RScript.r @ 42:9a47d7a552d6 draft

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author davidvanzessen
date Thu, 26 Oct 2017 09:08:37 -0400
parents a70dbcfa5d8a
children 2325074a8461
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1 # ---------------------- load/install packages ----------------------
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2
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3 if (!("gridExtra" %in% rownames(installed.packages()))) {
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4 install.packages("gridExtra", repos="http://cran.xl-mirror.nl/")
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5 }
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6 library(gridExtra)
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7 if (!("ggplot2" %in% rownames(installed.packages()))) {
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8 install.packages("ggplot2", repos="http://cran.xl-mirror.nl/")
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9 }
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10 library(ggplot2)
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11 if (!("plyr" %in% rownames(installed.packages()))) {
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12 install.packages("plyr", repos="http://cran.xl-mirror.nl/")
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13 }
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14 library(plyr)
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15
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16 if (!("data.table" %in% rownames(installed.packages()))) {
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17 install.packages("data.table", repos="http://cran.xl-mirror.nl/")
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18 }
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19 library(data.table)
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20
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21 if (!("reshape2" %in% rownames(installed.packages()))) {
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22 install.packages("reshape2", repos="http://cran.xl-mirror.nl/")
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23 }
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24 library(reshape2)
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25
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26 if (!("lymphclon" %in% rownames(installed.packages()))) {
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27 install.packages("lymphclon", repos="http://cran.xl-mirror.nl/")
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28 }
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29 library(lymphclon)
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30
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31 # ---------------------- parameters ----------------------
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32
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33 args <- commandArgs(trailingOnly = TRUE)
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35 infile = args[1] #path to input file
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36 outfile = args[2] #path to output file
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37 outdir = args[3] #path to output folder (html/images/data)
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38 clonaltype = args[4] #clonaltype definition, or 'none' for no unique filtering
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39 ct = unlist(strsplit(clonaltype, ","))
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40 species = args[5] #human or mouse
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41 locus = args[6] # IGH, IGK, IGL, TRB, TRA, TRG or TRD
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42 filterproductive = ifelse(args[7] == "yes", T, F) #should unproductive sequences be filtered out? (yes/no)
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43 clonality_method = args[8]
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44
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45
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46 # ---------------------- Data preperation ----------------------
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47
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48 print("Report Clonality - Data preperation")
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49
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50 inputdata = read.table(infile, sep="\t", header=TRUE, fill=T, comment.char="", stringsAsFactors=F)
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52 inputdata$Sample = as.character(inputdata$Sample)
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55 print(paste("nrows: ", nrow(inputdata)))
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56
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57 setwd(outdir)
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58
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59 # remove weird rows
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60 inputdata = inputdata[inputdata$Sample != "",]
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61
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62 print(paste("nrows: ", nrow(inputdata)))
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63
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64 #remove the allele from the V,D and J genes
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65 inputdata$Top.V.Gene = gsub("[*]([0-9]+)", "", inputdata$Top.V.Gene)
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66 inputdata$Top.D.Gene = gsub("[*]([0-9]+)", "", inputdata$Top.D.Gene)
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67 inputdata$Top.J.Gene = gsub("[*]([0-9]+)", "", inputdata$Top.J.Gene)
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68
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69 print(paste("nrows: ", nrow(inputdata)))
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70
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71 #filter uniques
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72 inputdata.removed = inputdata[NULL,]
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74 print(paste("nrows: ", nrow(inputdata)))
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75
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76 inputdata$clonaltype = 1:nrow(inputdata)
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77
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78 #keep track of the count of sequences in samples or samples/replicates for the front page overview
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79 input.sample.count = data.frame(data.table(inputdata)[, list(All=.N), by=c("Sample")])
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80 input.rep.count = data.frame(data.table(inputdata)[, list(All=.N), by=c("Sample", "Replicate")])
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81
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82 PRODF = inputdata
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83 UNPROD = inputdata
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84 if(filterproductive){
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85 if("Functionality" %in% colnames(inputdata)) { # "Functionality" is an IMGT column
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86 #PRODF = inputdata[inputdata$Functionality == "productive" | inputdata$Functionality == "productive (see comment)", ]
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87 PRODF = inputdata[inputdata$Functionality %in% c("productive (see comment)","productive"),]
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88
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89 PRODF.count = data.frame(data.table(PRODF)[, list(count=.N), by=c("Sample")])
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90
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91 UNPROD = inputdata[inputdata$Functionality %in% c("unproductive (see comment)","unproductive"), ]
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92 } else {
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93 PRODF = inputdata[inputdata$VDJ.Frame != "In-frame with stop codon" & inputdata$VDJ.Frame != "Out-of-frame" & inputdata$CDR3.Found.How != "NOT_FOUND" , ]
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94 UNPROD = inputdata[!(inputdata$VDJ.Frame != "In-frame with stop codon" & inputdata$VDJ.Frame != "Out-of-frame" & inputdata$CDR3.Found.How != "NOT_FOUND" ), ]
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95 }
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96 }
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98 for(i in 1:nrow(UNPROD)){
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99 if(!is.numeric(UNPROD[i,"CDR3.Length"])){
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100 UNPROD[i,"CDR3.Length"] = 0
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101 }
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102 }
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103
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104 prod.sample.count = data.frame(data.table(PRODF)[, list(Productive=.N), by=c("Sample")])
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105 prod.rep.count = data.frame(data.table(PRODF)[, list(Productive=.N), by=c("Sample", "Replicate")])
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106
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107 unprod.sample.count = data.frame(data.table(UNPROD)[, list(Unproductive=.N), by=c("Sample")])
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108 unprod.rep.count = data.frame(data.table(UNPROD)[, list(Unproductive=.N), by=c("Sample", "Replicate")])
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109
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110 clonalityFrame = PRODF
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111
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112 #remove duplicates based on the clonaltype
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113 if(clonaltype != "none"){
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114 clonaltype = paste(clonaltype, ",Sample", sep="") #add sample column to clonaltype, unique within samples
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115 PRODF$clonaltype = do.call(paste, c(PRODF[unlist(strsplit(clonaltype, ","))], sep = ":"))
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116 PRODF = PRODF[!duplicated(PRODF$clonaltype), ]
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117
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118 UNPROD$clonaltype = do.call(paste, c(UNPROD[unlist(strsplit(clonaltype, ","))], sep = ":"))
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119 UNPROD = UNPROD[!duplicated(UNPROD$clonaltype), ]
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120
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121 #again for clonalityFrame but with sample+replicate
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122 clonalityFrame$clonaltype = do.call(paste, c(clonalityFrame[unlist(strsplit(clonaltype, ","))], sep = ":"))
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123 clonalityFrame$clonality_clonaltype = do.call(paste, c(clonalityFrame[unlist(strsplit(paste(clonaltype, ",Replicate", sep=""), ","))], sep = ":"))
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124 clonalityFrame = clonalityFrame[!duplicated(clonalityFrame$clonality_clonaltype), ]
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125 }
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126
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127 if(nrow(PRODF) == 0){
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128 stop("No sequences left after filtering")
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129 }
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130
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131 prod.unique.sample.count = data.frame(data.table(PRODF)[, list(Productive_unique=.N), by=c("Sample")])
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132 prod.unique.rep.count = data.frame(data.table(PRODF)[, list(Productive_unique=.N), by=c("Sample", "Replicate")])
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133
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134 unprod.unique.sample.count = data.frame(data.table(UNPROD)[, list(Unproductive_unique=.N), by=c("Sample")])
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135 unprod.unique.rep.count = data.frame(data.table(UNPROD)[, list(Unproductive_unique=.N), by=c("Sample", "Replicate")])
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136
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138 PRODF$freq = 1
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139
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140 if(any(grepl(pattern="_", x=PRODF$ID))){ #the frequency can be stored in the ID with the pattern ".*_freq_.*"
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141 PRODF$freq = gsub("^[0-9]+_", "", PRODF$ID)
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142 PRODF$freq = gsub("_.*", "", PRODF$freq)
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143 PRODF$freq = as.numeric(PRODF$freq)
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144 if(any(is.na(PRODF$freq))){ #if there was an "_" in the ID, but not the frequency, go back to frequency of 1 for every sequence
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145 PRODF$freq = 1
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146 }
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147 }
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148
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149 #make a names list with sample -> color
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150 naive.colors = c('blue4', 'darkred', 'olivedrab3', 'red', 'gray74', 'darkviolet', 'lightblue1', 'gold', 'chartreuse2', 'pink', 'Paleturquoise3', 'Chocolate1', 'Yellow', 'Deeppink3', 'Mediumorchid1', 'Darkgreen', 'Blue', 'Gray36', 'Hotpink', 'Yellow4')
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151 unique.samples = unique(PRODF$Sample)
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152
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153 if(length(unique.samples) <= length(naive.colors)){
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154 sample.colors = naive.colors[1:length(unique.samples)]
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155 } else {
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156 sample.colors = rainbow(length(unique.samples))
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157 }
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158
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159 names(sample.colors) = unique.samples
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160
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161 print("Sample.colors")
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162 print(sample.colors)
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163
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164
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165 #write the complete dataset that is left over, will be the input if 'none' for clonaltype and 'no' for filterproductive
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166 write.table(PRODF, "allUnique.txt", sep="\t",quote=F,row.names=F,col.names=T)
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167 #write.table(PRODF, "allUnique.csv", sep=",",quote=F,row.names=F,col.names=T)
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168 write.table(UNPROD, "allUnproductive.txt", sep="\t",quote=F,row.names=F,col.names=T)
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170 print("SAMPLE TABLE:")
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171 print(table(PRODF$Sample))
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172
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173 #write the samples to a file
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174 sampleFile <- file("samples.txt")
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175 un = unique(inputdata$Sample)
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176 un = paste(un, sep="\n")
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177 writeLines(un, sampleFile)
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parents:
diff changeset
178 close(sampleFile)
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parents:
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179
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parents:
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180 # ---------------------- Counting the productive/unproductive and unique sequences ----------------------
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parents:
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181
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parents:
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182 print("Report Clonality - counting productive/unproductive/unique")
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davidvanzessen
parents:
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183
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davidvanzessen
parents:
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184 #create the table on the overview page with the productive/unique counts per sample/replicate
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parents:
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185 #first for sample
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diff changeset
186
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parents:
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187 sample.count = merge(input.sample.count, prod.sample.count, by="Sample", all.x=T)
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davidvanzessen
parents:
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188 sample.count$perc_prod = round(sample.count$Productive / sample.count$All * 100)
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davidvanzessen
parents:
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189 sample.count = merge(sample.count, prod.unique.sample.count, by="Sample", all.x=T)
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davidvanzessen
parents:
diff changeset
190 sample.count$perc_prod_un = round(sample.count$Productive_unique / sample.count$All * 100)
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davidvanzessen
parents:
diff changeset
191
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davidvanzessen
parents:
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192 sample.count = merge(sample.count , unprod.sample.count, by="Sample", all.x=T)
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davidvanzessen
parents:
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193 sample.count$perc_unprod = round(sample.count$Unproductive / sample.count$All * 100)
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davidvanzessen
parents:
diff changeset
194 sample.count = merge(sample.count, unprod.unique.sample.count, by="Sample", all.x=T)
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davidvanzessen
parents:
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195 sample.count$perc_unprod_un = round(sample.count$Unproductive_unique / sample.count$All * 100)
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davidvanzessen
parents:
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196
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davidvanzessen
parents:
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197 #then sample/replicate
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parents:
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198 rep.count = merge(input.rep.count, prod.rep.count, by=c("Sample", "Replicate"), all.x=T)
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diff changeset
199
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diff changeset
200 print(rep.count)
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parents: 38
diff changeset
201
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parents: 38
diff changeset
202 fltr = is.na(rep.count$Productive)
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parents: 38
diff changeset
203 if(any(fltr)){
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parents: 38
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204 rep.count[fltr,"Productive"] = 0
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parents: 38
diff changeset
205 }
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parents: 38
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206
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diff changeset
207 print(rep.count)
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208
5
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parents:
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209 rep.count$perc_prod = round(rep.count$Productive / rep.count$All * 100)
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davidvanzessen
parents:
diff changeset
210 rep.count = merge(rep.count, prod.unique.rep.count, by=c("Sample", "Replicate"), all.x=T)
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davidvanzessen
parents:
diff changeset
211 rep.count$perc_prod_un = round(rep.count$Productive_unique / rep.count$All * 100)
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davidvanzessen
parents:
diff changeset
212
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davidvanzessen
parents:
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213 rep.count = merge(rep.count, unprod.rep.count, by=c("Sample", "Replicate"), all.x=T)
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davidvanzessen
parents:
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214 rep.count$perc_unprod = round(rep.count$Unproductive / rep.count$All * 100)
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davidvanzessen
parents:
diff changeset
215 rep.count = merge(rep.count, unprod.unique.rep.count, by=c("Sample", "Replicate"), all.x=T)
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davidvanzessen
parents:
diff changeset
216 rep.count$perc_unprod_un = round(rep.count$Unproductive_unique / rep.count$All * 100)
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davidvanzessen
parents:
diff changeset
217
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davidvanzessen
parents:
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218 rep.count$Sample = paste(rep.count$Sample, rep.count$Replicate, sep="_")
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davidvanzessen
parents:
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219 rep.count = rep.count[,names(rep.count) != "Replicate"]
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davidvanzessen
parents:
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220
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davidvanzessen
parents:
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221 count = rbind(sample.count, rep.count)
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davidvanzessen
parents:
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222
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davidvanzessen
parents:
diff changeset
223
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davidvanzessen
parents:
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224
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parents:
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225 write.table(x=count, file="productive_counting.txt", sep=",",quote=F,row.names=F,col.names=F)
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davidvanzessen
parents:
diff changeset
226
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davidvanzessen
parents:
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227 # ---------------------- V+J+CDR3 sequence count ----------------------
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davidvanzessen
parents:
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228
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parents:
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229 VJCDR3.count = data.frame(table(clonalityFrame$Top.V.Gene, clonalityFrame$Top.J.Gene, clonalityFrame$CDR3.Seq.DNA))
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davidvanzessen
parents:
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230 names(VJCDR3.count) = c("Top.V.Gene", "Top.J.Gene", "CDR3.Seq.DNA", "Count")
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davidvanzessen
parents:
diff changeset
231
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davidvanzessen
parents:
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232 VJCDR3.count = VJCDR3.count[VJCDR3.count$Count > 0,]
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davidvanzessen
parents:
diff changeset
233 VJCDR3.count = VJCDR3.count[order(-VJCDR3.count$Count),]
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davidvanzessen
parents:
diff changeset
234
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davidvanzessen
parents:
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235 write.table(x=VJCDR3.count, file="VJCDR3_count.txt", sep="\t",quote=F,row.names=F,col.names=T)
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davidvanzessen
parents:
diff changeset
236
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davidvanzessen
parents:
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237 # ---------------------- Frequency calculation for V, D and J ----------------------
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davidvanzessen
parents:
diff changeset
238
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davidvanzessen
parents:
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239 print("Report Clonality - frequency calculation V, D and J")
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davidvanzessen
parents:
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240
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davidvanzessen
parents:
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241 PRODFV = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Sample", "Top.V.Gene")])
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davidvanzessen
parents:
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242 Total = ddply(PRODFV, .(Sample), function(x) data.frame(Total = sum(x$Length)))
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davidvanzessen
parents:
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243 PRODFV = merge(PRODFV, Total, by.x='Sample', by.y='Sample', all.x=TRUE)
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davidvanzessen
parents:
diff changeset
244 PRODFV = ddply(PRODFV, c("Sample", "Top.V.Gene"), summarise, relFreq= (Length*100 / Total))
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parents:
diff changeset
245
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davidvanzessen
parents:
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246 PRODFD = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Sample", "Top.D.Gene")])
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davidvanzessen
parents:
diff changeset
247 Total = ddply(PRODFD, .(Sample), function(x) data.frame(Total = sum(x$Length)))
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davidvanzessen
parents:
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248 PRODFD = merge(PRODFD, Total, by.x='Sample', by.y='Sample', all.x=TRUE)
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davidvanzessen
parents:
diff changeset
249 PRODFD = ddply(PRODFD, c("Sample", "Top.D.Gene"), summarise, relFreq= (Length*100 / Total))
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davidvanzessen
parents:
diff changeset
250
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davidvanzessen
parents:
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251 PRODFJ = data.frame(data.table(PRODF)[, list(Length=sum(freq)), by=c("Sample", "Top.J.Gene")])
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davidvanzessen
parents:
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252 Total = ddply(PRODFJ, .(Sample), function(x) data.frame(Total = sum(x$Length)))
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davidvanzessen
parents:
diff changeset
253 PRODFJ = merge(PRODFJ, Total, by.x='Sample', by.y='Sample', all.x=TRUE)
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davidvanzessen
parents:
diff changeset
254 PRODFJ = ddply(PRODFJ, c("Sample", "Top.J.Gene"), summarise, relFreq= (Length*100 / Total))
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davidvanzessen
parents:
diff changeset
255
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davidvanzessen
parents:
diff changeset
256 # ---------------------- Setting up the gene names for the different species/loci ----------------------
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davidvanzessen
parents:
diff changeset
257
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davidvanzessen
parents:
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258 print("Report Clonality - getting genes for species/loci")
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davidvanzessen
parents:
diff changeset
259
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davidvanzessen
parents:
diff changeset
260 Vchain = ""
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davidvanzessen
parents:
diff changeset
261 Dchain = ""
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davidvanzessen
parents:
diff changeset
262 Jchain = ""
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davidvanzessen
parents:
diff changeset
263
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davidvanzessen
parents:
diff changeset
264 if(species == "custom"){
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davidvanzessen
parents:
diff changeset
265 print("Custom genes: ")
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davidvanzessen
parents:
diff changeset
266 splt = unlist(strsplit(locus, ";"))
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davidvanzessen
parents:
diff changeset
267 print(paste("V:", splt[1]))
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davidvanzessen
parents:
diff changeset
268 print(paste("D:", splt[2]))
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davidvanzessen
parents:
diff changeset
269 print(paste("J:", splt[3]))
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davidvanzessen
parents:
diff changeset
270
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davidvanzessen
parents:
diff changeset
271 Vchain = unlist(strsplit(splt[1], ","))
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davidvanzessen
parents:
diff changeset
272 Vchain = data.frame(v.name = Vchain, chr.orderV = 1:length(Vchain))
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davidvanzessen
parents:
diff changeset
273
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davidvanzessen
parents:
diff changeset
274 Dchain = unlist(strsplit(splt[2], ","))
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davidvanzessen
parents:
diff changeset
275 if(length(Dchain) > 0){
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davidvanzessen
parents:
diff changeset
276 Dchain = data.frame(v.name = Dchain, chr.orderD = 1:length(Dchain))
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davidvanzessen
parents:
diff changeset
277 } else {
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davidvanzessen
parents:
diff changeset
278 Dchain = data.frame(v.name = character(0), chr.orderD = numeric(0))
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davidvanzessen
parents:
diff changeset
279 }
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davidvanzessen
parents:
diff changeset
280
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davidvanzessen
parents:
diff changeset
281 Jchain = unlist(strsplit(splt[3], ","))
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davidvanzessen
parents:
diff changeset
282 Jchain = data.frame(v.name = Jchain, chr.orderJ = 1:length(Jchain))
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davidvanzessen
parents:
diff changeset
283
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davidvanzessen
parents:
diff changeset
284 } else {
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davidvanzessen
parents:
diff changeset
285 genes = read.table("genes.txt", sep="\t", header=TRUE, fill=T, comment.char="")
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davidvanzessen
parents:
diff changeset
286
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davidvanzessen
parents:
diff changeset
287 Vchain = genes[grepl(species, genes$Species) & genes$locus == locus & genes$region == "V",c("IMGT.GENE.DB", "chr.order")]
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davidvanzessen
parents:
diff changeset
288 colnames(Vchain) = c("v.name", "chr.orderV")
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davidvanzessen
parents:
diff changeset
289 Dchain = genes[grepl(species, genes$Species) & genes$locus == locus & genes$region == "D",c("IMGT.GENE.DB", "chr.order")]
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davidvanzessen
parents:
diff changeset
290 colnames(Dchain) = c("v.name", "chr.orderD")
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davidvanzessen
parents:
diff changeset
291 Jchain = genes[grepl(species, genes$Species) & genes$locus == locus & genes$region == "J",c("IMGT.GENE.DB", "chr.order")]
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davidvanzessen
parents:
diff changeset
292 colnames(Jchain) = c("v.name", "chr.orderJ")
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davidvanzessen
parents:
diff changeset
293 }
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davidvanzessen
parents:
diff changeset
294 useD = TRUE
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davidvanzessen
parents:
diff changeset
295 if(nrow(Dchain) == 0){
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davidvanzessen
parents:
diff changeset
296 useD = FALSE
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davidvanzessen
parents:
diff changeset
297 cat("No D Genes in this species/locus")
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davidvanzessen
parents:
diff changeset
298 }
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davidvanzessen
parents:
diff changeset
299 print(paste(nrow(Vchain), "genes in V"))
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davidvanzessen
parents:
diff changeset
300 print(paste(nrow(Dchain), "genes in D"))
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davidvanzessen
parents:
diff changeset
301 print(paste(nrow(Jchain), "genes in J"))
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davidvanzessen
parents:
diff changeset
302
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davidvanzessen
parents:
diff changeset
303 # ---------------------- merge with the frequency count ----------------------
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davidvanzessen
parents:
diff changeset
304
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davidvanzessen
parents:
diff changeset
305 PRODFV = merge(PRODFV, Vchain, by.x='Top.V.Gene', by.y='v.name', all.x=TRUE)
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davidvanzessen
parents:
diff changeset
306
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davidvanzessen
parents:
diff changeset
307 PRODFD = merge(PRODFD, Dchain, by.x='Top.D.Gene', by.y='v.name', all.x=TRUE)
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davidvanzessen
parents:
diff changeset
308
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davidvanzessen
parents:
diff changeset
309 PRODFJ = merge(PRODFJ, Jchain, by.x='Top.J.Gene', by.y='v.name', all.x=TRUE)
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davidvanzessen
parents:
diff changeset
310
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davidvanzessen
parents:
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311 # ---------------------- Create the V, D and J frequency plots and write the data.frame for every plot to a file ----------------------
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davidvanzessen
parents:
diff changeset
312
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davidvanzessen
parents:
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313 print("Report Clonality - V, D and J frequency plots")
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davidvanzessen
parents:
diff changeset
314
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davidvanzessen
parents:
diff changeset
315 pV = ggplot(PRODFV)
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davidvanzessen
parents:
diff changeset
316 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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parents: 6
diff changeset
317 pV = pV + xlab("Summary of V gene") + ylab("Frequency") + ggtitle("Relative frequency of V gene usage") + scale_fill_manual(values=sample.colors)
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parents: 6
diff changeset
318 pV = pV + theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
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parents: 17
diff changeset
319 write.table(x=PRODFV, file="VFrequency.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
320
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davidvanzessen
parents:
diff changeset
321 png("VPlot.png",width = 1280, height = 720)
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davidvanzessen
parents:
diff changeset
322 pV
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parents: 30
diff changeset
323 dev.off()
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parents: 30
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324
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diff changeset
325 ggsave("VPlot.pdf", pV, width=13, height=7)
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davidvanzessen
parents:
diff changeset
326
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davidvanzessen
parents:
diff changeset
327 if(useD){
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davidvanzessen
parents:
diff changeset
328 pD = ggplot(PRODFD)
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davidvanzessen
parents:
diff changeset
329 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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parents: 6
diff changeset
330 pD = pD + xlab("Summary of D gene") + ylab("Frequency") + ggtitle("Relative frequency of D gene usage") + scale_fill_manual(values=sample.colors)
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parents: 6
diff changeset
331 pD = pD + theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
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parents: 17
diff changeset
332 write.table(x=PRODFD, file="DFrequency.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
333
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davidvanzessen
parents:
diff changeset
334 png("DPlot.png",width = 800, height = 600)
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davidvanzessen
parents:
diff changeset
335 print(pD)
32
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parents: 30
diff changeset
336 dev.off()
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parents: 30
diff changeset
337
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parents: 30
diff changeset
338 ggsave("DPlot.pdf", pD, width=10, height=7)
5
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davidvanzessen
parents:
diff changeset
339 }
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davidvanzessen
parents:
diff changeset
340
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davidvanzessen
parents:
diff changeset
341 pJ = ggplot(PRODFJ)
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davidvanzessen
parents:
diff changeset
342 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))
8
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davidvanzessen
parents: 6
diff changeset
343 pJ = pJ + xlab("Summary of J gene") + ylab("Frequency") + ggtitle("Relative frequency of J gene usage") + scale_fill_manual(values=sample.colors)
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davidvanzessen
parents: 6
diff changeset
344 pJ = pJ + theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
18
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davidvanzessen
parents: 17
diff changeset
345 write.table(x=PRODFJ, file="JFrequency.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
346
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davidvanzessen
parents:
diff changeset
347 png("JPlot.png",width = 800, height = 600)
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davidvanzessen
parents:
diff changeset
348 pJ
32
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davidvanzessen
parents: 30
diff changeset
349 dev.off()
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davidvanzessen
parents: 30
diff changeset
350
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davidvanzessen
parents: 30
diff changeset
351 ggsave("JPlot.pdf", pJ)
5
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davidvanzessen
parents:
diff changeset
352
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davidvanzessen
parents:
diff changeset
353 # ---------------------- Now the frequency plots of the V, D and J families ----------------------
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davidvanzessen
parents:
diff changeset
354
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davidvanzessen
parents:
diff changeset
355 print("Report Clonality - V, D and J family plots")
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davidvanzessen
parents:
diff changeset
356
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davidvanzessen
parents:
diff changeset
357 VGenes = PRODF[,c("Sample", "Top.V.Gene")]
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davidvanzessen
parents:
diff changeset
358 VGenes$Top.V.Gene = gsub("-.*", "", VGenes$Top.V.Gene)
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davidvanzessen
parents:
diff changeset
359 VGenes = data.frame(data.table(VGenes)[, list(Count=.N), by=c("Sample", "Top.V.Gene")])
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davidvanzessen
parents:
diff changeset
360 TotalPerSample = data.frame(data.table(VGenes)[, list(total=sum(.SD$Count)), by=Sample])
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davidvanzessen
parents:
diff changeset
361 VGenes = merge(VGenes, TotalPerSample, by="Sample")
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davidvanzessen
parents:
diff changeset
362 VGenes$Frequency = VGenes$Count * 100 / VGenes$total
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davidvanzessen
parents:
diff changeset
363 VPlot = ggplot(VGenes)
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davidvanzessen
parents:
diff changeset
364 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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davidvanzessen
parents:
diff changeset
365 ggtitle("Distribution of V gene families") +
8
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davidvanzessen
parents: 6
diff changeset
366 ylab("Percentage of sequences") +
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davidvanzessen
parents: 6
diff changeset
367 scale_fill_manual(values=sample.colors) +
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davidvanzessen
parents: 6
diff changeset
368 theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
5
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davidvanzessen
parents:
diff changeset
369 png("VFPlot.png")
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davidvanzessen
parents:
diff changeset
370 VPlot
32
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davidvanzessen
parents: 30
diff changeset
371 dev.off()
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davidvanzessen
parents: 30
diff changeset
372 ggsave("VFPlot.pdf", VPlot)
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davidvanzessen
parents: 30
diff changeset
373
18
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davidvanzessen
parents: 17
diff changeset
374 write.table(x=VGenes, file="VFFrequency.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
375
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davidvanzessen
parents:
diff changeset
376 if(useD){
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davidvanzessen
parents:
diff changeset
377 DGenes = PRODF[,c("Sample", "Top.D.Gene")]
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davidvanzessen
parents:
diff changeset
378 DGenes$Top.D.Gene = gsub("-.*", "", DGenes$Top.D.Gene)
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davidvanzessen
parents:
diff changeset
379 DGenes = data.frame(data.table(DGenes)[, list(Count=.N), by=c("Sample", "Top.D.Gene")])
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davidvanzessen
parents:
diff changeset
380 TotalPerSample = data.frame(data.table(DGenes)[, list(total=sum(.SD$Count)), by=Sample])
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davidvanzessen
parents:
diff changeset
381 DGenes = merge(DGenes, TotalPerSample, by="Sample")
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davidvanzessen
parents:
diff changeset
382 DGenes$Frequency = DGenes$Count * 100 / DGenes$total
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davidvanzessen
parents:
diff changeset
383 DPlot = ggplot(DGenes)
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davidvanzessen
parents:
diff changeset
384 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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davidvanzessen
parents:
diff changeset
385 ggtitle("Distribution of D gene families") +
8
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davidvanzessen
parents: 6
diff changeset
386 ylab("Percentage of sequences") +
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davidvanzessen
parents: 6
diff changeset
387 scale_fill_manual(values=sample.colors) +
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davidvanzessen
parents: 6
diff changeset
388 theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
5
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davidvanzessen
parents:
diff changeset
389 png("DFPlot.png")
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davidvanzessen
parents:
diff changeset
390 print(DPlot)
32
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davidvanzessen
parents: 30
diff changeset
391 dev.off()
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davidvanzessen
parents: 30
diff changeset
392
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davidvanzessen
parents: 30
diff changeset
393 ggsave("DFPlot.pdf", DPlot)
18
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davidvanzessen
parents: 17
diff changeset
394 write.table(x=DGenes, file="DFFrequency.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
395 }
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davidvanzessen
parents:
diff changeset
396
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davidvanzessen
parents:
diff changeset
397 # ---------------------- Plotting the cdr3 length ----------------------
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davidvanzessen
parents:
diff changeset
398
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davidvanzessen
parents:
diff changeset
399 print("Report Clonality - CDR3 length plot")
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davidvanzessen
parents:
diff changeset
400
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davidvanzessen
parents: 8
diff changeset
401 CDR3Length = data.frame(data.table(PRODF)[, list(Count=.N), by=c("Sample", "CDR3.Length")])
5
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davidvanzessen
parents:
diff changeset
402 TotalPerSample = data.frame(data.table(CDR3Length)[, list(total=sum(.SD$Count)), by=Sample])
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davidvanzessen
parents:
diff changeset
403 CDR3Length = merge(CDR3Length, TotalPerSample, by="Sample")
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davidvanzessen
parents:
diff changeset
404 CDR3Length$Frequency = CDR3Length$Count * 100 / CDR3Length$total
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davidvanzessen
parents:
diff changeset
405 CDR3LengthPlot = ggplot(CDR3Length)
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davidvanzessen
parents: 14
diff changeset
406 CDR3LengthPlot = CDR3LengthPlot + geom_bar(aes( x = factor(reorder(CDR3.Length, as.numeric(CDR3.Length))), y = Frequency, fill = Sample), stat='identity', position='dodge' ) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
5
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davidvanzessen
parents:
diff changeset
407 ggtitle("Length distribution of CDR3") +
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davidvanzessen
parents:
diff changeset
408 xlab("CDR3 Length") +
8
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
409 ylab("Percentage of sequences") +
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davidvanzessen
parents: 6
diff changeset
410 scale_fill_manual(values=sample.colors) +
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davidvanzessen
parents: 6
diff changeset
411 theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
5
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davidvanzessen
parents:
diff changeset
412 png("CDR3LengthPlot.png",width = 1280, height = 720)
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davidvanzessen
parents:
diff changeset
413 CDR3LengthPlot
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davidvanzessen
parents:
diff changeset
414 dev.off()
32
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davidvanzessen
parents: 30
diff changeset
415
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davidvanzessen
parents: 30
diff changeset
416 ggsave("CDR3LengthPlot.pdf", CDR3LengthPlot, width=12, height=7)
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davidvanzessen
parents: 30
diff changeset
417
24
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davidvanzessen
parents: 20
diff changeset
418 write.table(x=CDR3Length, file="CDR3LengthPlot.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
419
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davidvanzessen
parents:
diff changeset
420 # ---------------------- Plot the heatmaps ----------------------
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davidvanzessen
parents:
diff changeset
421
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davidvanzessen
parents:
diff changeset
422 #get the reverse order for the V and D genes
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davidvanzessen
parents:
diff changeset
423 revVchain = Vchain
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davidvanzessen
parents:
diff changeset
424 revDchain = Dchain
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davidvanzessen
parents:
diff changeset
425 revVchain$chr.orderV = rev(revVchain$chr.orderV)
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davidvanzessen
parents:
diff changeset
426 revDchain$chr.orderD = rev(revDchain$chr.orderD)
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davidvanzessen
parents:
diff changeset
427
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davidvanzessen
parents:
diff changeset
428 if(useD){
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davidvanzessen
parents:
diff changeset
429 print("Report Clonality - Heatmaps VD")
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davidvanzessen
parents:
diff changeset
430 plotVD <- function(dat){
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davidvanzessen
parents:
diff changeset
431 if(length(dat[,1]) == 0){
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davidvanzessen
parents:
diff changeset
432 return()
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davidvanzessen
parents:
diff changeset
433 }
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davidvanzessen
parents:
diff changeset
434
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davidvanzessen
parents:
diff changeset
435 img = ggplot() +
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davidvanzessen
parents:
diff changeset
436 geom_tile(data=dat, aes(x=factor(reorder(Top.D.Gene, chr.orderD)), y=factor(reorder(Top.V.Gene, chr.orderV)), fill=relLength)) +
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
437 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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davidvanzessen
parents:
diff changeset
438 scale_fill_gradient(low="gold", high="blue", na.value="white") +
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
439 ggtitle(paste(unique(dat$Sample), " (N=" , sum(dat$Length, na.rm=T) ,")", sep="")) +
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davidvanzessen
parents:
diff changeset
440 xlab("D genes") +
9
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davidvanzessen
parents: 8
diff changeset
441 ylab("V Genes") +
14
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davidvanzessen
parents: 13
diff changeset
442 theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), panel.grid.major = element_line(colour = "gainsboro"))
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
443
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davidvanzessen
parents:
diff changeset
444 png(paste("HeatmapVD_", unique(dat[3])[1,1] , ".png", sep=""), width=150+(15*length(Dchain$v.name)), height=100+(15*length(Vchain$v.name)))
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davidvanzessen
parents:
diff changeset
445 print(img)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
446 dev.off()
32
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davidvanzessen
parents: 30
diff changeset
447
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davidvanzessen
parents: 30
diff changeset
448 ggsave(paste("HeatmapVD_", unique(dat[3])[1,1] , ".pdf", sep=""), img, height=13, width=8)
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davidvanzessen
parents: 30
diff changeset
449
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
450 write.table(x=acast(dat, Top.V.Gene~Top.D.Gene, value.var="Length"), file=paste("HeatmapVD_", unique(dat[3])[1,1], ".txt", sep=""), sep="\t",quote=F,row.names=T,col.names=NA)
5
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davidvanzessen
parents:
diff changeset
451 }
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davidvanzessen
parents:
diff changeset
452
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davidvanzessen
parents:
diff changeset
453 VandDCount = data.frame(data.table(PRODF)[, list(Length=.N), by=c("Top.V.Gene", "Top.D.Gene", "Sample")])
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davidvanzessen
parents:
diff changeset
454
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davidvanzessen
parents:
diff changeset
455 VandDCount$l = log(VandDCount$Length)
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davidvanzessen
parents:
diff changeset
456 maxVD = data.frame(data.table(VandDCount)[, list(max=max(l)), by=c("Sample")])
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davidvanzessen
parents:
diff changeset
457 VandDCount = merge(VandDCount, maxVD, by.x="Sample", by.y="Sample", all.x=T)
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davidvanzessen
parents:
diff changeset
458 VandDCount$relLength = VandDCount$l / VandDCount$max
6
d001d0c05dbe Uploaded
davidvanzessen
parents: 5
diff changeset
459 check = is.nan(VandDCount$relLength)
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davidvanzessen
parents: 5
diff changeset
460 if(any(check)){
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davidvanzessen
parents: 5
diff changeset
461 VandDCount[check,"relLength"] = 0
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davidvanzessen
parents: 5
diff changeset
462 }
5
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davidvanzessen
parents:
diff changeset
463
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davidvanzessen
parents:
diff changeset
464 cartegianProductVD = expand.grid(Top.V.Gene = Vchain$v.name, Top.D.Gene = Dchain$v.name)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
465
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davidvanzessen
parents:
diff changeset
466 completeVD = merge(VandDCount, cartegianProductVD, by.x=c("Top.V.Gene", "Top.D.Gene"), by.y=c("Top.V.Gene", "Top.D.Gene"), all=TRUE)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
467
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davidvanzessen
parents:
diff changeset
468 completeVD = merge(completeVD, revVchain, by.x="Top.V.Gene", by.y="v.name", all.x=TRUE)
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davidvanzessen
parents:
diff changeset
469
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davidvanzessen
parents:
diff changeset
470 completeVD = merge(completeVD, Dchain, by.x="Top.D.Gene", by.y="v.name", all.x=TRUE)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
471
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
472 fltr = is.nan(completeVD$relLength)
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davidvanzessen
parents:
diff changeset
473 if(all(fltr)){
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davidvanzessen
parents:
diff changeset
474 completeVD[fltr,"relLength"] = 0
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davidvanzessen
parents:
diff changeset
475 }
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davidvanzessen
parents:
diff changeset
476
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davidvanzessen
parents:
diff changeset
477 VDList = split(completeVD, f=completeVD[,"Sample"])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
478 lapply(VDList, FUN=plotVD)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
479 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
480
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
481 print("Report Clonality - Heatmaps VJ")
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davidvanzessen
parents:
diff changeset
482
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davidvanzessen
parents:
diff changeset
483 plotVJ <- function(dat){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
484 if(length(dat[,1]) == 0){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
485 return()
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
486 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
487 cat(paste(unique(dat[3])[1,1]))
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davidvanzessen
parents:
diff changeset
488 img = ggplot() +
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davidvanzessen
parents:
diff changeset
489 geom_tile(data=dat, aes(x=factor(reorder(Top.J.Gene, chr.orderJ)), y=factor(reorder(Top.V.Gene, chr.orderV)), fill=relLength)) +
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
490 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
491 scale_fill_gradient(low="gold", high="blue", na.value="white") +
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
492 ggtitle(paste(unique(dat$Sample), " (N=" , sum(dat$Length, na.rm=T) ,")", sep="")) +
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
493 xlab("J genes") +
9
efa1f5a17b6e Uploaded
davidvanzessen
parents: 8
diff changeset
494 ylab("V Genes") +
14
15961ca8d9ce Uploaded
davidvanzessen
parents: 13
diff changeset
495 theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), panel.grid.major = element_line(colour = "gainsboro"))
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
496
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
497 png(paste("HeatmapVJ_", unique(dat[3])[1,1] , ".png", sep=""), width=150+(15*length(Jchain$v.name)), height=100+(15*length(Vchain$v.name)))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
498 print(img)
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davidvanzessen
parents:
diff changeset
499 dev.off()
32
7c33029fd63d Uploaded
davidvanzessen
parents: 30
diff changeset
500
7c33029fd63d Uploaded
davidvanzessen
parents: 30
diff changeset
501 ggsave(paste("HeatmapVJ_", unique(dat[3])[1,1] , ".pdf", sep=""), img, height=11, width=4)
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davidvanzessen
parents: 30
diff changeset
502
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
503 write.table(x=acast(dat, Top.V.Gene~Top.J.Gene, value.var="Length"), file=paste("HeatmapVJ_", unique(dat[3])[1,1], ".txt", sep=""), sep="\t",quote=F,row.names=T,col.names=NA)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
504 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
505
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
506 VandJCount = data.frame(data.table(PRODF)[, list(Length=.N), by=c("Top.V.Gene", "Top.J.Gene", "Sample")])
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davidvanzessen
parents:
diff changeset
507
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davidvanzessen
parents:
diff changeset
508 VandJCount$l = log(VandJCount$Length)
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davidvanzessen
parents:
diff changeset
509 maxVJ = data.frame(data.table(VandJCount)[, list(max=max(l)), by=c("Sample")])
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davidvanzessen
parents:
diff changeset
510 VandJCount = merge(VandJCount, maxVJ, by.x="Sample", by.y="Sample", all.x=T)
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davidvanzessen
parents:
diff changeset
511 VandJCount$relLength = VandJCount$l / VandJCount$max
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davidvanzessen
parents:
diff changeset
512
6
d001d0c05dbe Uploaded
davidvanzessen
parents: 5
diff changeset
513 check = is.nan(VandJCount$relLength)
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davidvanzessen
parents: 5
diff changeset
514 if(any(check)){
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davidvanzessen
parents: 5
diff changeset
515 VandJCount[check,"relLength"] = 0
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davidvanzessen
parents: 5
diff changeset
516 }
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davidvanzessen
parents: 5
diff changeset
517
5
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davidvanzessen
parents:
diff changeset
518 cartegianProductVJ = expand.grid(Top.V.Gene = Vchain$v.name, Top.J.Gene = Jchain$v.name)
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davidvanzessen
parents:
diff changeset
519
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davidvanzessen
parents:
diff changeset
520 completeVJ = merge(VandJCount, cartegianProductVJ, all.y=TRUE)
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davidvanzessen
parents:
diff changeset
521 completeVJ = merge(completeVJ, revVchain, by.x="Top.V.Gene", by.y="v.name", all.x=TRUE)
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davidvanzessen
parents:
diff changeset
522 completeVJ = merge(completeVJ, Jchain, by.x="Top.J.Gene", by.y="v.name", all.x=TRUE)
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davidvanzessen
parents:
diff changeset
523
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davidvanzessen
parents:
diff changeset
524 fltr = is.nan(completeVJ$relLength)
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davidvanzessen
parents:
diff changeset
525 if(any(fltr)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
526 completeVJ[fltr,"relLength"] = 1
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davidvanzessen
parents:
diff changeset
527 }
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davidvanzessen
parents:
diff changeset
528
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davidvanzessen
parents:
diff changeset
529 VJList = split(completeVJ, f=completeVJ[,"Sample"])
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davidvanzessen
parents:
diff changeset
530 lapply(VJList, FUN=plotVJ)
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davidvanzessen
parents:
diff changeset
531
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
532
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
533
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davidvanzessen
parents:
diff changeset
534 if(useD){
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davidvanzessen
parents:
diff changeset
535 print("Report Clonality - Heatmaps DJ")
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davidvanzessen
parents:
diff changeset
536 plotDJ <- function(dat){
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davidvanzessen
parents:
diff changeset
537 if(length(dat[,1]) == 0){
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davidvanzessen
parents:
diff changeset
538 return()
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davidvanzessen
parents:
diff changeset
539 }
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davidvanzessen
parents:
diff changeset
540 img = ggplot() +
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davidvanzessen
parents:
diff changeset
541 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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davidvanzessen
parents:
diff changeset
542 theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
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davidvanzessen
parents:
diff changeset
543 scale_fill_gradient(low="gold", high="blue", na.value="white") +
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davidvanzessen
parents:
diff changeset
544 ggtitle(paste(unique(dat$Sample), " (N=" , sum(dat$Length, na.rm=T) ,")", sep="")) +
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davidvanzessen
parents:
diff changeset
545 xlab("J genes") +
9
efa1f5a17b6e Uploaded
davidvanzessen
parents: 8
diff changeset
546 ylab("D Genes") +
14
15961ca8d9ce Uploaded
davidvanzessen
parents: 13
diff changeset
547 theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), panel.grid.major = element_line(colour = "gainsboro"))
5
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davidvanzessen
parents:
diff changeset
548
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davidvanzessen
parents:
diff changeset
549 png(paste("HeatmapDJ_", unique(dat[3])[1,1] , ".png", sep=""), width=150+(15*length(Jchain$v.name)), height=100+(15*length(Dchain$v.name)))
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davidvanzessen
parents:
diff changeset
550 print(img)
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davidvanzessen
parents:
diff changeset
551 dev.off()
32
7c33029fd63d Uploaded
davidvanzessen
parents: 30
diff changeset
552
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davidvanzessen
parents: 30
diff changeset
553 ggsave(paste("HeatmapDJ_", unique(dat[3])[1,1] , ".pdf", sep=""), img, width=4, height=7)
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davidvanzessen
parents: 30
diff changeset
554
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
555 write.table(x=acast(dat, Top.D.Gene~Top.J.Gene, value.var="Length"), file=paste("HeatmapDJ_", unique(dat[3])[1,1], ".txt", sep=""), sep="\t",quote=F,row.names=T,col.names=NA)
5
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davidvanzessen
parents:
diff changeset
556 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
557
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davidvanzessen
parents:
diff changeset
558
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davidvanzessen
parents:
diff changeset
559 DandJCount = data.frame(data.table(PRODF)[, list(Length=.N), by=c("Top.D.Gene", "Top.J.Gene", "Sample")])
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davidvanzessen
parents:
diff changeset
560
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davidvanzessen
parents:
diff changeset
561 DandJCount$l = log(DandJCount$Length)
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davidvanzessen
parents:
diff changeset
562 maxDJ = data.frame(data.table(DandJCount)[, list(max=max(l)), by=c("Sample")])
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davidvanzessen
parents:
diff changeset
563 DandJCount = merge(DandJCount, maxDJ, by.x="Sample", by.y="Sample", all.x=T)
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davidvanzessen
parents:
diff changeset
564 DandJCount$relLength = DandJCount$l / DandJCount$max
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davidvanzessen
parents:
diff changeset
565
6
d001d0c05dbe Uploaded
davidvanzessen
parents: 5
diff changeset
566 check = is.nan(DandJCount$relLength)
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davidvanzessen
parents: 5
diff changeset
567 if(any(check)){
d001d0c05dbe Uploaded
davidvanzessen
parents: 5
diff changeset
568 DandJCount[check,"relLength"] = 0
d001d0c05dbe Uploaded
davidvanzessen
parents: 5
diff changeset
569 }
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davidvanzessen
parents: 5
diff changeset
570
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
571 cartegianProductDJ = expand.grid(Top.D.Gene = Dchain$v.name, Top.J.Gene = Jchain$v.name)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
572
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davidvanzessen
parents:
diff changeset
573 completeDJ = merge(DandJCount, cartegianProductDJ, all.y=TRUE)
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davidvanzessen
parents:
diff changeset
574 completeDJ = merge(completeDJ, revDchain, by.x="Top.D.Gene", by.y="v.name", all.x=TRUE)
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davidvanzessen
parents:
diff changeset
575 completeDJ = merge(completeDJ, Jchain, by.x="Top.J.Gene", by.y="v.name", all.x=TRUE)
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davidvanzessen
parents:
diff changeset
576
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davidvanzessen
parents:
diff changeset
577 fltr = is.nan(completeDJ$relLength)
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davidvanzessen
parents:
diff changeset
578 if(any(fltr)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
579 completeDJ[fltr, "relLength"] = 1
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davidvanzessen
parents:
diff changeset
580 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
581
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
582 DJList = split(completeDJ, f=completeDJ[,"Sample"])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
583 lapply(DJList, FUN=plotDJ)
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davidvanzessen
parents:
diff changeset
584 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
585
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
586
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
587 # ---------------------- output tables for the circos plots ----------------------
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davidvanzessen
parents:
diff changeset
588
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davidvanzessen
parents:
diff changeset
589 print("Report Clonality - Circos data")
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
590
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davidvanzessen
parents:
diff changeset
591 for(smpl in unique(PRODF$Sample)){
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davidvanzessen
parents:
diff changeset
592 PRODF.sample = PRODF[PRODF$Sample == smpl,]
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davidvanzessen
parents:
diff changeset
593
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davidvanzessen
parents:
diff changeset
594 fltr = PRODF.sample$Top.V.Gene == ""
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
595 if(any(fltr, na.rm=T)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
596 PRODF.sample[fltr, "Top.V.Gene"] = "NA"
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
597 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
598
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
599 fltr = PRODF.sample$Top.D.Gene == ""
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
600 if(any(fltr, na.rm=T)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
601 PRODF.sample[fltr, "Top.D.Gene"] = "NA"
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
602 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
603
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
604 fltr = PRODF.sample$Top.J.Gene == ""
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
605 if(any(fltr, na.rm=T)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
606 PRODF.sample[fltr, "Top.J.Gene"] = "NA"
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
607 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
608
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
609 v.d = table(PRODF.sample$Top.V.Gene, PRODF.sample$Top.D.Gene)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
610 v.j = table(PRODF.sample$Top.V.Gene, PRODF.sample$Top.J.Gene)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
611 d.j = table(PRODF.sample$Top.D.Gene, PRODF.sample$Top.J.Gene)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
612
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
613 write.table(v.d, file=paste(smpl, "_VD_circos.txt", sep=""), sep="\t", quote=F, row.names=T, col.names=NA)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
614 write.table(v.j, file=paste(smpl, "_VJ_circos.txt", sep=""), sep="\t", quote=F, row.names=T, col.names=NA)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
615 write.table(d.j, file=paste(smpl, "_DJ_circos.txt", sep=""), sep="\t", quote=F, row.names=T, col.names=NA)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
616 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
617
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
618 # ---------------------- calculating the clonality score ----------------------
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
619
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
620 if("Replicate" %in% colnames(inputdata)) #can only calculate clonality score when replicate information is available
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
621 {
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
622 print("Report Clonality - Clonality")
18
5d11c9139a55 Uploaded
davidvanzessen
parents: 17
diff changeset
623 write.table(clonalityFrame, "clonalityComplete.txt", sep="\t",quote=F,row.names=F,col.names=T)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
624 if(clonality_method == "boyd"){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
625 samples = split(clonalityFrame, clonalityFrame$Sample, drop=T)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
626
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
627 for (sample in samples){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
628 res = data.frame(paste=character(0))
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davidvanzessen
parents:
diff changeset
629 sample_id = unique(sample$Sample)[[1]]
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
630 for(replicate in unique(sample$Replicate)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
631 tmp = sample[sample$Replicate == replicate,]
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davidvanzessen
parents:
diff changeset
632 clone_table = data.frame(table(tmp$clonaltype))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
633 clone_col_name = paste("V", replicate, sep="")
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
634 colnames(clone_table) = c("paste", clone_col_name)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
635 res = merge(res, clone_table, by="paste", all=T)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
636 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
637
17
da95be204ebc Uploaded
davidvanzessen
parents: 15
diff changeset
638 res[is.na(res)] = 0
da95be204ebc Uploaded
davidvanzessen
parents: 15
diff changeset
639
20
9185c3dfc679 Uploaded
davidvanzessen
parents: 18
diff changeset
640 write.table(res, file=paste("raw_clonality_", sample_id, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=F)
9185c3dfc679 Uploaded
davidvanzessen
parents: 18
diff changeset
641 write.table(as.matrix(res[,2:ncol(res)]), file=paste("raw_clonality2_", sample_id, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=F)
9185c3dfc679 Uploaded
davidvanzessen
parents: 18
diff changeset
642
9185c3dfc679 Uploaded
davidvanzessen
parents: 18
diff changeset
643 res = read.table(paste("raw_clonality_", sample_id, ".txt", sep=""), header=F, sep="\t", quote="", stringsAsFactors=F, fill=T, comment.char="")
17
da95be204ebc Uploaded
davidvanzessen
parents: 15
diff changeset
644
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
645 infer.result = infer.clonality(as.matrix(res[,2:ncol(res)]))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
646
13
d3ebaa2d2fe0 Uploaded
davidvanzessen
parents: 9
diff changeset
647 #print(infer.result)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
648
20
9185c3dfc679 Uploaded
davidvanzessen
parents: 18
diff changeset
649 write.table(data.table(infer.result[[12]]), file=paste("lymphclon_clonality_", sample_id, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=F)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
650
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
651 res$type = rowSums(res[,2:ncol(res)])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
652
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
653 coincidence.table = data.frame(table(res$type))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
654 colnames(coincidence.table) = c("Coincidence Type", "Raw Coincidence Freq")
20
9185c3dfc679 Uploaded
davidvanzessen
parents: 18
diff changeset
655 write.table(coincidence.table, file=paste("lymphclon_coincidences_", sample_id, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=T)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
656 }
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
657 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
658 clonalFreq = data.frame(data.table(clonalityFrame)[, list(Type=.N), by=c("Sample", "clonaltype")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
659
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
660 #write files for every coincidence group of >1
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
661 samples = unique(clonalFreq$Sample)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
662 for(sample in samples){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
663 clonalFreqSample = clonalFreq[clonalFreq$Sample == sample,]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
664 if(max(clonalFreqSample$Type) > 1){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
665 for(i in 2:max(clonalFreqSample$Type)){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
666 clonalFreqSampleType = clonalFreqSample[clonalFreqSample$Type == i,]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
667 clonalityFrame.sub = clonalityFrame[clonalityFrame$clonaltype %in% clonalFreqSampleType$clonaltype,]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
668 clonalityFrame.sub = clonalityFrame.sub[order(clonalityFrame.sub$clonaltype),]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
669 write.table(clonalityFrame.sub, file=paste("coincidences_", sample, "_", i, ".txt", sep=""), sep="\t",quote=F,row.names=F,col.names=T)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
670 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
671 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
672 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
673
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
674 clonalFreqCount = data.frame(data.table(clonalFreq)[, list(Count=.N), by=c("Sample", "Type")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
675 clonalFreqCount$realCount = clonalFreqCount$Type * clonalFreqCount$Count
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davidvanzessen
parents: 25
diff changeset
676 clonalSum = data.frame(data.table(clonalFreqCount)[, list(Reads=sum(realCount)), by=c("Sample")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
677 clonalFreqCount = merge(clonalFreqCount, clonalSum, by.x="Sample", by.y="Sample")
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
678
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
679 ct = c('Type\tWeight\n2\t1\n3\t3\n4\t6\n5\t10\n6\t15')
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
680 tcct = textConnection(ct)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
681 CT = read.table(tcct, sep="\t", header=TRUE)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
682 close(tcct)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
683 clonalFreqCount = merge(clonalFreqCount, CT, by.x="Type", by.y="Type", all.x=T)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
684 clonalFreqCount$WeightedCount = clonalFreqCount$Count * clonalFreqCount$Weight
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
685
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
686 ReplicateReads = data.frame(data.table(clonalityFrame)[, list(Type=.N), by=c("Sample", "Replicate", "clonaltype")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
687 ReplicateReads = data.frame(data.table(ReplicateReads)[, list(Reads=.N), by=c("Sample", "Replicate")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
688 clonalFreqCount$Reads = as.numeric(clonalFreqCount$Reads)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
689 ReplicateReads$Reads = as.numeric(ReplicateReads$Reads)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
690 ReplicateReads$squared = as.numeric(ReplicateReads$Reads * ReplicateReads$Reads)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
691
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
692 ReplicatePrint <- function(dat){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
693 write.table(dat[-1], paste("ReplicateReads_", unique(dat[1])[1,1] , ".txt", sep=""), sep="\t",quote=F,na="-",row.names=F,col.names=F)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
694 }
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
695
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
696 ReplicateSplit = split(ReplicateReads, f=ReplicateReads[,"Sample"])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
697 lapply(ReplicateSplit, FUN=ReplicatePrint)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
698
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
699 ReplicateReads = data.frame(data.table(ReplicateReads)[, list(ReadsSum=sum(as.numeric(Reads)), ReadsSquaredSum=sum(as.numeric(squared))), by=c("Sample")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
700 clonalFreqCount = merge(clonalFreqCount, ReplicateReads, by.x="Sample", by.y="Sample", all.x=T)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
701
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
702 ReplicateSumPrint <- function(dat){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
703 write.table(dat[-1], paste("ReplicateSumReads_", unique(dat[1])[1,1] , ".txt", sep=""), sep="\t",quote=F,na="-",row.names=F,col.names=F)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
704 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
705
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
706 ReplicateSumSplit = split(ReplicateReads, f=ReplicateReads[,"Sample"])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
707 lapply(ReplicateSumSplit, FUN=ReplicateSumPrint)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
708
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
709 clonalFreqCountSum = data.frame(data.table(clonalFreqCount)[, list(Numerator=sum(WeightedCount, na.rm=T)), by=c("Sample")])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
710 clonalFreqCount = merge(clonalFreqCount, clonalFreqCountSum, by.x="Sample", by.y="Sample", all.x=T)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
711 clonalFreqCount$ReadsSum = as.numeric(clonalFreqCount$ReadsSum) #prevent integer overflow
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
712 clonalFreqCount$Denominator = (((clonalFreqCount$ReadsSum * clonalFreqCount$ReadsSum) - clonalFreqCount$ReadsSquaredSum) / 2)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
713 clonalFreqCount$Result = (clonalFreqCount$Numerator + 1) / (clonalFreqCount$Denominator + 1)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
714
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
715 ClonalityScorePrint <- function(dat){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
716 write.table(dat$Result, paste("ClonalityScore_", unique(dat[1])[1,1] , ".txt", sep=""), sep="\t",quote=F,na="-",row.names=F,col.names=F)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
717 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
718
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
719 clonalityScore = clonalFreqCount[c("Sample", "Result")]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
720 clonalityScore = unique(clonalityScore)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
721
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
722 clonalityScoreSplit = split(clonalityScore, f=clonalityScore[,"Sample"])
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
723 lapply(clonalityScoreSplit, FUN=ClonalityScorePrint)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
724
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
725 clonalityOverview = clonalFreqCount[c("Sample", "Type", "Count", "Weight", "WeightedCount")]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
726
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
727
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
728
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
729 ClonalityOverviewPrint <- function(dat){
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
730 dat = dat[order(dat[,2]),]
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
731 write.table(dat[-1], paste("ClonalityOverView_", unique(dat[1])[1,1] , ".txt", sep=""), sep="\t",quote=F,na="-",row.names=F,col.names=F)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
732 }
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
733
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
734 clonalityOverviewSplit = split(clonalityOverview, f=clonalityOverview$Sample)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
735 lapply(clonalityOverviewSplit, FUN=ClonalityOverviewPrint)
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
736
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
737 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
738
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
739 bak = PRODF
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
740 bakun = UNPROD
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
741
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
742 imgtcolumns = c("X3V.REGION.trimmed.nt.nb","P3V.nt.nb", "N1.REGION.nt.nb", "P5D.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "P3D.nt.nb", "N2.REGION.nt.nb", "P5J.nt.nb", "X5J.REGION.trimmed.nt.nb", "X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb")
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
743 if(all(imgtcolumns %in% colnames(inputdata)))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
744 {
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
745 print("found IMGT columns, running junction analysis")
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
746
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
747 #ensure certain columns are in the data (files generated with older versions of IMGT Loader)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
748 col.checks = c("N.REGION.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb")
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
749 for(col.check in col.checks){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
750 if(!(col.check %in% names(PRODF))){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
751 print(paste(col.check, "not found adding new column"))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
752 if(nrow(PRODF) > 0){ #because R is anoying...
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
753 PRODF[,col.check] = 0
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
754 } else {
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
755 PRODF = cbind(PRODF, data.frame(N3.REGION.nt.nb=numeric(0), N4.REGION.nt.nb=numeric(0)))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
756 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
757 if(nrow(UNPROD) > 0){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
758 UNPROD[,col.check] = 0
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
759 } else {
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
760 UNPROD = cbind(UNPROD, data.frame(N3.REGION.nt.nb=numeric(0), N4.REGION.nt.nb=numeric(0)))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
761 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
762 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
763 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
764
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
765 PRODF.with.D = PRODF[nchar(PRODF$Top.D.Gene, keepNA=F) > 2,]
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
766 PRODF.no.D = PRODF[nchar(PRODF$Top.D.Gene, keepNA=F) < 4,]
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
767 write.table(PRODF.no.D, "productive_no_D.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=T)
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
768
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
769 UNPROD.with.D = UNPROD[nchar(UNPROD$Top.D.Gene, keepNA=F) > 2,]
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
770 UNPROD.no.D = UNPROD[nchar(UNPROD$Top.D.Gene, keepNA=F) < 4,]
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
771 write.table(UNPROD.no.D, "unproductive_no_D.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=T)
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
772
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
773 num_median = function(x, na.rm=T) { as.numeric(median(x, na.rm=na.rm)) }
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
774
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
775 newData = data.frame(data.table(PRODF.with.D)[,list(unique=.N,
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
776 VH.DEL=mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
777 P1=mean(.SD$P3V.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
778 N1=mean(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
779 P2=mean(.SD$P5D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
780 DEL.DH=mean(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
781 DH.DEL=mean(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
782 P3=mean(.SD$P3D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
783 N2=mean(rowSums(.SD[,c("N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
784 P4=mean(.SD$P5J.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
785 DEL.JH=mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
786 Total.Del=mean(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
787 Total.N=mean(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
788 Total.P=mean(rowSums(.SD[,c("P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
789 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
790 by=c("Sample")])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
791 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
792 write.table(newData, "junctionAnalysisProd_mean_wD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
793
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
794 newData = data.frame(data.table(PRODF.with.D)[,list(unique=.N,
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
795 VH.DEL=num_median(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
796 P1=num_median(.SD$P3V.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
797 N1=num_median(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
798 P2=num_median(.SD$P5D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
799 DEL.DH=num_median(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
800 DH.DEL=num_median(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
801 P3=num_median(.SD$P3D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
802 N2=num_median(rowSums(.SD[,c("N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
803 P4=num_median(.SD$P5J.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
804 DEL.JH=num_median(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
805 Total.Del=num_median(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
806 Total.N=num_median(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
807 Total.P=num_median(rowSums(.SD[,c("P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
808 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
809 by=c("Sample")])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
810 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
811 write.table(newData, "junctionAnalysisProd_median_wD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
812
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
813 newData = data.frame(data.table(UNPROD.with.D)[,list(unique=.N,
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
814 VH.DEL=mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
815 P1=mean(.SD$P3V.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
816 N1=mean(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
817 P2=mean(.SD$P5D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
818 DEL.DH=mean(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
819 DH.DEL=mean(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
820 P3=mean(.SD$P3D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
821 N2=mean(rowSums(.SD[,c("N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
822 P4=mean(.SD$P5J.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
823 DEL.JH=mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
824 Total.Del=mean(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
825 Total.N=mean(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
826 Total.P=mean(rowSums(.SD[,c("P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
827 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
828 by=c("Sample")])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
829 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
830 write.table(newData, "junctionAnalysisUnProd_mean_wD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
831
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
832 newData = data.frame(data.table(UNPROD.with.D)[,list(unique=.N,
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
833 VH.DEL=num_median(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
834 P1=num_median(.SD$P3V.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
835 N1=num_median(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
836 P2=num_median(.SD$P5D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
837 DEL.DH=num_median(.SD$X5D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
838 DH.DEL=num_median(.SD$X3D.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
839 P3=num_median(.SD$P3D.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
840 N2=num_median(rowSums(.SD[,c("N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
841 P4=num_median(.SD$P5J.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
842 DEL.JH=num_median(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
843 Total.Del=num_median(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5D.REGION.trimmed.nt.nb", "X3D.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
844 Total.N=num_median(rowSums(.SD[,c("N.REGION.nt.nb", "N1.REGION.nt.nb", "N2.REGION.nt.nb", "N3.REGION.nt.nb", "N4.REGION.nt.nb"), with=F], na.rm=T)),
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
845 Total.P=num_median(rowSums(.SD[,c("P3V.nt.nb", "P5D.nt.nb", "P3D.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
846 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
847 by=c("Sample")])
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
848 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
849 write.table(newData, "junctionAnalysisUnProd_median_wD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
850
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
851 #---------------- again for no-D
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
852
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
853 newData = data.frame(data.table(PRODF.no.D)[,list(unique=.N,
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
854 VH.DEL=mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
855 P1=mean(.SD$P3V.nt.nb, na.rm=T),
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
856 N1=mean(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
857 P2=mean(.SD$P5J.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
858 DEL.JH=mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
859 Total.Del=mean(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
860 Total.N=mean(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
861 Total.P=mean(rowSums(.SD[,c("P3V.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
862 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
863 by=c("Sample")])
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
864 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
865 write.table(newData, "junctionAnalysisProd_mean_nD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
866
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
867 newData = data.frame(data.table(PRODF.no.D)[,list(unique=.N,
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
868 VH.DEL=num_median(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
869 P1=num_median(.SD$P3V.nt.nb, na.rm=T),
30
b50965edac24 Uploaded
davidvanzessen
parents: 29
diff changeset
870 N1=num_median(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
871 P2=num_median(.SD$P5J.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
872 DEL.JH=num_median(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
873 Total.Del=num_median(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
30
b50965edac24 Uploaded
davidvanzessen
parents: 29
diff changeset
874 Total.N=num_median(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
875 Total.P=num_median(rowSums(.SD[,c("P3V.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
876 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
877 by=c("Sample")])
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
878 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
879 write.table(newData, "junctionAnalysisProd_median_nD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
880
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
881 newData = data.frame(data.table(UNPROD.no.D)[,list(unique=.N,
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
882 VH.DEL=mean(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
883 P1=mean(.SD$P3V.nt.nb, na.rm=T),
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
884 N1=mean(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
885 P2=mean(.SD$P5J.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
886 DEL.JH=mean(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
887 Total.Del=mean(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
888 Total.N=mean(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
889 Total.P=mean(rowSums(.SD[,c("P3V.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
890 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
891 by=c("Sample")])
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
892 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
893 write.table(newData, "junctionAnalysisUnProd_mean_nD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
894
26
28fbbdfd7a87 Uploaded
davidvanzessen
parents: 25
diff changeset
895
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
896 newData = data.frame(data.table(UNPROD.no.D)[,list(unique=.N,
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
897 VH.DEL=num_median(.SD$X3V.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
898 P1=num_median(.SD$P3V.nt.nb, na.rm=T),
30
b50965edac24 Uploaded
davidvanzessen
parents: 29
diff changeset
899 N1=num_median(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
900 P2=num_median(.SD$P5J.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
901 DEL.JH=num_median(.SD$X5J.REGION.trimmed.nt.nb, na.rm=T),
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
902 Total.Del=num_median(rowSums(.SD[,c("X3V.REGION.trimmed.nt.nb", "X5J.REGION.trimmed.nt.nb"), with=F], na.rm=T)),
30
b50965edac24 Uploaded
davidvanzessen
parents: 29
diff changeset
903 Total.N=num_median(.SD$N.REGION.nt.nb, na.rm=T),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
904 Total.P=num_median(rowSums(.SD[,c("P3V.nt.nb", "P5J.nt.nb"), with=F], na.rm=T)),
38
b6936fb52ab9 Uploaded
davidvanzessen
parents: 37
diff changeset
905 Median.CDR3.l=as.double(median(as.numeric(.SD$CDR3.Length), na.rm=T))),
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
906 by=c("Sample")])
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
907 newData[,sapply(newData, is.numeric)] = round(newData[,sapply(newData, is.numeric)],1)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
908 write.table(newData, "junctionAnalysisUnProd_median_nD.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
909 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
910
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
911 PRODF = bak
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
912 UNPROD = bakun
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
913
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
914
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
915 # ---------------------- D reading frame ----------------------
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
916
8
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
917 D.REGION.reading.frame = PRODF[,c("Sample", "D.REGION.reading.frame")]
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
918
8
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
919 chck = is.na(D.REGION.reading.frame$D.REGION.reading.frame)
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
920 if(any(chck)){
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
921 D.REGION.reading.frame[chck,"D.REGION.reading.frame"] = "No D"
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
922 }
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
923
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
924 D.REGION.reading.frame.1 = data.frame(data.table(D.REGION.reading.frame)[, list(Freq=.N), by=c("Sample", "D.REGION.reading.frame")])
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
925
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
926 D.REGION.reading.frame.2 = data.frame(data.table(D.REGION.reading.frame)[, list(sample.sum=sum(as.numeric(.SD$D.REGION.reading.frame), na.rm=T)), by=c("Sample")])
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
927
24
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
928 D.REGION.reading.frame = merge(D.REGION.reading.frame.1, D.REGION.reading.frame.2, by="Sample")
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
929
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
930 D.REGION.reading.frame$percentage = round(D.REGION.reading.frame$Freq / D.REGION.reading.frame$sample.sum * 100, 1)
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
931
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
932 write.table(D.REGION.reading.frame, "DReadingFrame.txt" , sep="\t",quote=F,row.names=F,col.names=T)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
933
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
934 D.REGION.reading.frame = ggplot(D.REGION.reading.frame)
29
1f83e14f173b Uploaded
davidvanzessen
parents: 26
diff changeset
935 D.REGION.reading.frame = D.REGION.reading.frame + geom_bar(aes( x = D.REGION.reading.frame, y = percentage, fill=Sample), stat='identity', position='dodge' ) + ggtitle("D reading frame") + xlab("Frame") + ylab("Frequency")
8
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
936 D.REGION.reading.frame = D.REGION.reading.frame + scale_fill_manual(values=sample.colors)
8cbc1a8d27ae Uploaded
davidvanzessen
parents: 6
diff changeset
937 D.REGION.reading.frame = D.REGION.reading.frame + theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), axis.text.x = element_text(angle = 45, hjust = 1), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
938
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
939 png("DReadingFrame.png")
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
940 D.REGION.reading.frame
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
941 dev.off()
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
942
32
7c33029fd63d Uploaded
davidvanzessen
parents: 30
diff changeset
943 ggsave("DReadingFrame.pdf", D.REGION.reading.frame)
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
944
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
945 # ---------------------- AA composition in CDR3 ----------------------
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
946
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
947 AACDR3 = PRODF[,c("Sample", "CDR3.Seq")]
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
948
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
949 TotalPerSample = data.frame(data.table(AACDR3)[, list(total=sum(nchar(as.character(.SD$CDR3.Seq)))), by=Sample])
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
950
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
951 AAfreq = list()
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
952
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
953 for(i in 1:nrow(TotalPerSample)){
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
954 sample = TotalPerSample$Sample[i]
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
955 AAfreq[[i]] = data.frame(table(unlist(strsplit(as.character(AACDR3[AACDR3$Sample == sample,c("CDR3.Seq")]), ""))))
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
956 AAfreq[[i]]$Sample = sample
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
957 }
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
958
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davidvanzessen
parents:
diff changeset
959 AAfreq = ldply(AAfreq, data.frame)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
960 AAfreq = merge(AAfreq, TotalPerSample, by="Sample", all.x = T)
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davidvanzessen
parents:
diff changeset
961 AAfreq$freq_perc = as.numeric(AAfreq$Freq / AAfreq$total * 100)
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davidvanzessen
parents:
diff changeset
962
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davidvanzessen
parents:
diff changeset
963
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davidvanzessen
parents:
diff changeset
964 AAorder = read.table(sep="\t", header=TRUE, text="order.aa\tAA\n1\tR\n2\tK\n3\tN\n4\tD\n5\tQ\n6\tE\n7\tH\n8\tP\n9\tY\n10\tW\n11\tS\n12\tT\n13\tG\n14\tA\n15\tM\n16\tC\n17\tF\n18\tL\n19\tV\n20\tI")
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davidvanzessen
parents:
diff changeset
965 AAfreq = merge(AAfreq, AAorder, by.x='Var1', by.y='AA', all.x=TRUE)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
966
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
967 AAfreq = AAfreq[!is.na(AAfreq$order.aa),]
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
968
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davidvanzessen
parents:
diff changeset
969 AAfreqplot = ggplot(AAfreq)
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davidvanzessen
parents:
diff changeset
970 AAfreqplot = AAfreqplot + geom_bar(aes( x=factor(reorder(Var1, order.aa)), y = freq_perc, fill = Sample), stat='identity', position='dodge' )
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davidvanzessen
parents:
diff changeset
971 AAfreqplot = AAfreqplot + annotate("rect", xmin = 0.5, xmax = 2.5, ymin = 0, ymax = Inf, fill = "red", alpha = 0.2)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
972 AAfreqplot = AAfreqplot + annotate("rect", xmin = 3.5, xmax = 4.5, ymin = 0, ymax = Inf, fill = "blue", alpha = 0.2)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
973 AAfreqplot = AAfreqplot + annotate("rect", xmin = 5.5, xmax = 6.5, ymin = 0, ymax = Inf, fill = "blue", alpha = 0.2)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
974 AAfreqplot = AAfreqplot + annotate("rect", xmin = 6.5, xmax = 7.5, ymin = 0, ymax = Inf, fill = "red", alpha = 0.2)
8
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davidvanzessen
parents: 6
diff changeset
975 AAfreqplot = AAfreqplot + ggtitle("Amino Acid Composition in the CDR3") + xlab("Amino Acid, from Hydrophilic (left) to Hydrophobic (right)") + ylab("Percentage") + scale_fill_manual(values=sample.colors)
32
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davidvanzessen
parents: 30
diff changeset
976 AAfreqplot = AAfreqplot + theme(panel.background = element_rect(fill = "white", colour="black"),text = element_text(size=15, colour="black"), panel.grid.major.y = element_line(colour = "black"), panel.grid.major.x = element_blank())
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
977
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
978 png("AAComposition.png",width = 1280, height = 720)
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
979 AAfreqplot
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
980 dev.off()
32
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davidvanzessen
parents: 30
diff changeset
981
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davidvanzessen
parents: 30
diff changeset
982 ggsave("AAComposition.pdf", AAfreqplot, width=12, height=7)
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davidvanzessen
parents: 30
diff changeset
983
18
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davidvanzessen
parents: 17
diff changeset
984 write.table(AAfreq, "AAComposition.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=T)
5
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davidvanzessen
parents:
diff changeset
985
8
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davidvanzessen
parents: 6
diff changeset
986 # ---------------------- AA median CDR3 length ----------------------
5
bcec7bb4e089 Uploaded
davidvanzessen
parents:
diff changeset
987
24
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davidvanzessen
parents: 20
diff changeset
988 median.aa.l = data.frame(data.table(PRODF)[, list(median=as.double(median(as.numeric(.SD$CDR3.Length, na.rm=T), na.rm=T))), by=c("Sample")])
d5d203d38c8a Uploaded
davidvanzessen
parents: 20
diff changeset
989 write.table(median.aa.l, "AAMedianBySample.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=F)
8
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davidvanzessen
parents: 6
diff changeset
990
25
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davidvanzessen
parents: 24
diff changeset
991
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davidvanzessen
parents: 24
diff changeset
992 #generate the "Sequences that are present in more than one replicate" dataset
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
993 clonaltype.in.replicates = inputdata
38
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davidvanzessen
parents: 37
diff changeset
994 clonaltype.in.replicates = clonaltype.in.replicates[clonaltype.in.replicates$Functionality %in% c("productive (see comment)","productive"),]
41
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davidvanzessen
parents: 40
diff changeset
995 clonaltype.in.replicates = clonaltype.in.replicates[!(is.na(clonaltype.in.replicates$ID) | is.na(clonaltype.in.replicates$Top.V.Gene) | is.na(clonaltype.in.replicates$Top.J.Gene)),]
25
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davidvanzessen
parents: 24
diff changeset
996 clonaltype = unlist(strsplit(clonaltype, ","))
37
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davidvanzessen
parents: 32
diff changeset
997
f37e072affc0 Uploaded
davidvanzessen
parents: 32
diff changeset
998 clonaltype.in.replicates$clonaltype = do.call(paste, c(clonaltype.in.replicates[c(clonaltype, "Replicate")], sep = ":"))
f37e072affc0 Uploaded
davidvanzessen
parents: 32
diff changeset
999
f37e072affc0 Uploaded
davidvanzessen
parents: 32
diff changeset
1000 clonaltype.in.replicates = clonaltype.in.replicates[!duplicated(clonaltype.in.replicates$clonaltype),]
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davidvanzessen
parents: 32
diff changeset
1001
25
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davidvanzessen
parents: 24
diff changeset
1002 clonaltype = clonaltype[-which(clonaltype == "Sample")]
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davidvanzessen
parents: 24
diff changeset
1003
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1004 clonaltype.in.replicates$clonaltype = do.call(paste, c(clonaltype.in.replicates[clonaltype], sep = ":"))
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1005 clonaltype.in.replicates = clonaltype.in.replicates[,c("clonaltype","Replicate", "ID", "Sequence", "Sample")]
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1006
41
a70dbcfa5d8a Uploaded
davidvanzessen
parents: 40
diff changeset
1007
a70dbcfa5d8a Uploaded
davidvanzessen
parents: 40
diff changeset
1008 write.table(clonaltype.in.replicates, "clonaltypes_replicates_before_table.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=T)
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davidvanzessen
parents: 40
diff changeset
1009
25
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davidvanzessen
parents: 24
diff changeset
1010 clonaltype.counts = data.frame(table(clonaltype.in.replicates$clonaltype))
41
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davidvanzessen
parents: 40
diff changeset
1011
a70dbcfa5d8a Uploaded
davidvanzessen
parents: 40
diff changeset
1012 write.table(clonaltype.counts, "clonaltypes_counts.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=T)
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davidvanzessen
parents: 40
diff changeset
1013
25
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davidvanzessen
parents: 24
diff changeset
1014 names(clonaltype.counts) = c("clonaltype", "coincidence")
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davidvanzessen
parents: 24
diff changeset
1015
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1016 clonaltype.counts = clonaltype.counts[clonaltype.counts$coincidence > 1,]
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1017
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1018 clonaltype.in.replicates = clonaltype.in.replicates[clonaltype.in.replicates$clonaltype %in% clonaltype.counts$clonaltype,]
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1019 clonaltype.in.replicates = merge(clonaltype.in.replicates, clonaltype.counts, by="clonaltype")
37
f37e072affc0 Uploaded
davidvanzessen
parents: 32
diff changeset
1020 clonaltype.in.replicates = clonaltype.in.replicates[order(-clonaltype.in.replicates$coincidence, clonaltype.in.replicates$clonaltype, clonaltype.in.replicates$Replicate),c("coincidence","clonaltype", "Sample", "Replicate", "ID", "Sequence")]
f37e072affc0 Uploaded
davidvanzessen
parents: 32
diff changeset
1021
25
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1022
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1023 write.table(clonaltype.in.replicates, "clonaltypes_replicates.txt" , sep="\t",quote=F,na="-",row.names=F,col.names=T)
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1024
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1025
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1026
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1027
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1028
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1029
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1030
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1031
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1032
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1033
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1034
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1035
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1036
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1037
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1038
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1039
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1040
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1041
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1042
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1043
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1044
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1045
94765af0db1f Uploaded
davidvanzessen
parents: 24
diff changeset
1046