|
0
|
1 args <- commandArgs(trailingOnly = TRUE)
|
|
|
2
|
|
|
3 inFile = args[1]
|
|
|
4 outDir = args[2]
|
|
3
|
5 logfile = args[3]
|
|
|
6 min_freq = as.numeric(args[4])
|
|
|
7 min_cells = as.numeric(args[5])
|
|
|
8
|
|
|
9 cat("<html><table><tr><td>Starting analysis</td></tr>", file=logfile, append=F)
|
|
0
|
10
|
|
4
|
11 library(ggplot2)
|
|
|
12 library(reshape2)
|
|
|
13 library(data.table)
|
|
|
14 library(grid)
|
|
|
15 library(parallel)
|
|
0
|
16 #require(xtable)
|
|
3
|
17 cat("<tr><td>Reading input</td></tr>", file=logfile, append=T)
|
|
13
|
18 dat = read.table(inFile, header=T, sep="\t", dec=".", fill=T, stringsAsFactors=F)
|
|
9
|
19 dat = dat[!is.na(dat$Patient),]
|
|
13
|
20 dat$Related_to_leukemia_clone = F
|
|
9
|
21
|
|
0
|
22 setwd(outDir)
|
|
3
|
23 cat("<tr><td>Selecting first V/J Genes</td></tr>", file=logfile, append=T)
|
|
2
|
24 dat$V_Segment_Major_Gene = as.factor(as.character(lapply(strsplit(as.character(dat$V_Segment_Major_Gene), "; "), "[[", 1)))
|
|
|
25 dat$J_Segment_Major_Gene = as.factor(as.character(lapply(strsplit(as.character(dat$J_Segment_Major_Gene), "; "), "[[", 1)))
|
|
|
26
|
|
3
|
27 cat("<tr><td>Calculating Frequency</td></tr>", file=logfile, append=T)
|
|
12
|
28
|
|
13
|
29 dat$Frequency = ((10^dat$Log10_Frequency)*100)
|
|
2
|
30
|
|
3
|
31 dat = dat[dat$Frequency >= min_freq,]
|
|
|
32
|
|
13
|
33 triplets = dat[grepl("VanDongen_cALL_14696", dat$Patient) | grepl("(16278)|(26402)|(26759)", dat$Sample),]
|
|
|
34
|
|
|
35 cat("<tr><td>Normalizing to lowest cell count within locus</td></tr>", file=logfile, append=T)
|
|
|
36
|
|
|
37 dat$locus_V = substring(dat$V_Segment_Major_Gene, 0, 4)
|
|
|
38 dat$locus_J = substring(dat$J_Segment_Major_Gene, 0, 4)
|
|
|
39 min_cell_count = data.frame(data.table(dat)[, list(min_cell_count=min(.SD$Cell_Count)), by=c("Patient", "locus_V", "locus_J")])
|
|
|
40
|
|
|
41 dat$min_cell_paste = paste(dat$Patient, dat$locus_V, dat$locus_J)
|
|
|
42 min_cell_count$min_cell_paste = paste(min_cell_count$Patient, min_cell_count$locus_V, min_cell_count$locus_J)
|
|
|
43
|
|
|
44 min_cell_count = min_cell_count[,c("min_cell_paste", "min_cell_count")]
|
|
|
45
|
|
|
46 dat = merge(dat, min_cell_count, by="min_cell_paste")
|
|
|
47
|
|
|
48 dat$normalized_read_count = round(dat$Clone_Molecule_Count_From_Spikes / dat$Cell_Count * dat$min_cell_count / 2, digits=2) #??????????????????????????????????? wel of geen / 2
|
|
|
49
|
|
3
|
50 dat = dat[dat$normalized_read_count >= min_cells,]
|
|
13
|
51
|
|
|
52 dat$paste = paste(dat$Sample, dat$Clone_Sequence)
|
|
9
|
53
|
|
22
|
54 patients = split(dat, dat$Patient, drop=T)
|
|
9
|
55 intervalReads = rev(c(0,10,25,50,100,250,500,750,1000,10000))
|
|
6
|
56 intervalFreq = rev(c(0,0.01,0.05,0.1,0.5,1,5))
|
|
0
|
57 V_Segments = c(".*", "IGHV", "IGHD", "IGKV", "IGKV", "IgKINTR", "TRGV", "TRDV", "TRDD" , "TRBV")
|
|
|
58 J_Segments = c(".*", ".*", ".*", "IGKJ", "KDE", ".*", ".*", ".*", ".*", ".*")
|
|
|
59 Titles = c("Total", "IGH-Vh-Jh", "IGH-Dh-Jh", "Vk-Jk", "Vk-Kde" , "Intron-Kde", "TCRG", "TCRD-Vd-Dd", "TCRD-Dd-Dd", "TCRB-Vb-Jb")
|
|
|
60 Titles = factor(Titles, levels=Titles)
|
|
|
61 TitlesOrder = data.frame("Title"=Titles, "TitlesOrder"=1:length(Titles))
|
|
|
62
|
|
|
63 patientCountOnColumn <- function(x, product, interval, on, appendtxt=F){
|
|
|
64 x$Sample = factor(x$Sample, levels=unique(x$Sample))
|
|
|
65 onShort = "reads"
|
|
|
66 if(on == "Frequency"){
|
|
|
67 onShort = "freq"
|
|
|
68 }
|
|
18
|
69 onx = paste(on, ".x", sep="")
|
|
|
70 ony = paste(on, ".y", sep="")
|
|
0
|
71 splt = split(x, x$Sample, drop=T)
|
|
4
|
72 type="pair"
|
|
2
|
73 if(length(splt) == 1){
|
|
3
|
74 print(paste(paste(x[1,which(colnames(x) == "Patient")]), "has one sample"))
|
|
4
|
75 splt[[2]] = data.frame("Patient" = character(0), "Receptor" = character(0), "Sample" = character(0), "Cell_Count" = numeric(0), "Clone_Molecule_Count_From_Spikes" = numeric(0), "Log10_Frequency" = numeric(0), "Total_Read_Count" = numeric(0), "dsMol_per_1e6_cells" = numeric(0), "J_Segment_Major_Gene" = character(0), "V_Segment_Major_Gene" = character(0), "Clone_Sequence" = character(0), "CDR3_Sense_Sequence" = character(0), "Related_to_leukemia_clone" = logical(0), "Frequency"= numeric(0), "normalized_read_count" = numeric(0), "paste" = character(0))
|
|
|
76 type="single"
|
|
2
|
77 }
|
|
0
|
78 patient1 = splt[[1]]
|
|
|
79 patient2 = splt[[2]]
|
|
|
80
|
|
|
81 threshholdIndex = which(colnames(product) == "interval")
|
|
|
82 V_SegmentIndex = which(colnames(product) == "V_Segments")
|
|
|
83 J_SegmentIndex = which(colnames(product) == "J_Segments")
|
|
|
84 titleIndex = which(colnames(product) == "Titles")
|
|
|
85 sampleIndex = which(colnames(x) == "Sample")
|
|
|
86 patientIndex = which(colnames(x) == "Patient")
|
|
|
87 oneSample = paste(patient1[1,sampleIndex], sep="")
|
|
|
88 twoSample = paste(patient2[1,sampleIndex], sep="")
|
|
|
89 patient = paste(x[1,patientIndex])
|
|
3
|
90
|
|
0
|
91 switched = F
|
|
|
92 if(length(grep(".*_Right$", twoSample)) == 1 || length(grep(".*_Dx_BM$", twoSample)) == 1 || length(grep(".*_Dx$", twoSample)) == 1 ){
|
|
|
93 tmp = twoSample
|
|
|
94 twoSample = oneSample
|
|
|
95 oneSample = tmp
|
|
|
96 tmp = patient1
|
|
|
97 patient1 = patient2
|
|
|
98 patient2 = tmp
|
|
|
99 switched = T
|
|
|
100 }
|
|
|
101 if(appendtxt){
|
|
4
|
102 cat(paste(patient, oneSample, twoSample, type, sep="\t"), file="patients.txt", append=T, sep="", fill=3)
|
|
0
|
103 }
|
|
3
|
104 cat(paste("<tr><td>", patient, "</td></tr>", sep=""), file=logfile, append=T)
|
|
9
|
105
|
|
12
|
106 #patient1$merge = paste(patient1$V_Segment_Major_Gene, patient1$J_Segment_Major_Gene, patient1$CDR3_Sense_Sequence)
|
|
|
107 #patient2$merge = paste(patient2$V_Segment_Major_Gene, patient2$J_Segment_Major_Gene, patient2$CDR3_Sense_Sequence)
|
|
13
|
108 patient1$merge = paste(patient1$Clone_Sequence)
|
|
|
109 patient2$merge = paste(patient2$Clone_Sequence)
|
|
9
|
110
|
|
12
|
111 #patientMerge = merge(patient1, patient2, by.x="merge", by.y="merge")
|
|
9
|
112 patientMerge = merge(patient1, patient2, by.x="merge", by.y="merge")
|
|
18
|
113 patientMerge$thresholdValue = pmax(patientMerge[,onx], patientMerge[,ony])
|
|
0
|
114 res1 = vector()
|
|
|
115 res2 = vector()
|
|
|
116 resBoth = vector()
|
|
|
117 read1Count = vector()
|
|
|
118 read2Count = vector()
|
|
2
|
119 locussum1 = vector()
|
|
|
120 locussum2 = vector()
|
|
9
|
121
|
|
|
122 print(patient)
|
|
0
|
123 #for(iter in 1){
|
|
|
124 for(iter in 1:length(product[,1])){
|
|
|
125 threshhold = product[iter,threshholdIndex]
|
|
|
126 V_Segment = paste(".*", as.character(product[iter,V_SegmentIndex]), ".*", sep="")
|
|
|
127 J_Segment = paste(".*", as.character(product[iter,J_SegmentIndex]), ".*", sep="")
|
|
18
|
128 #both = (grepl(V_Segment, patientMerge$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge$J_Segment_Major_Gene.x) & patientMerge[,onx] > threshhold & patientMerge[,ony] > threshhold) #both higher than threshold
|
|
|
129 both = (grepl(V_Segment, patientMerge$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge$J_Segment_Major_Gene.x) & patientMerge$thresholdValue > threshhold) #highest of both higher than threshold
|
|
19
|
130 one = (grepl(V_Segment, patient1$V_Segment_Major_Gene) & grepl(J_Segment, patient1$J_Segment_Major_Gene) & patient1[,on] > threshhold & !(patient1$Clone_Sequence %in% patientMerge[both,]$merge))
|
|
|
131 two = (grepl(V_Segment, patient2$V_Segment_Major_Gene) & grepl(J_Segment, patient2$J_Segment_Major_Gene) & patient2[,on] > threshhold & !(patient2$Clone_Sequence %in% patientMerge[both,]$merge))
|
|
14
|
132 read1Count = append(read1Count, sum(patient1[one,]$normalized_read_count))
|
|
|
133 read2Count = append(read2Count, sum(patient2[two,]$normalized_read_count))
|
|
0
|
134 res1 = append(res1, sum(one))
|
|
2
|
135 res2 = append(res2, sum(two))
|
|
0
|
136 resBoth = append(resBoth, sum(both))
|
|
2
|
137 locussum1 = append(locussum1, sum(patient1[(grepl(V_Segment, patient1$V_Segment_Major_Gene) & grepl(J_Segment, patient1$J_Segment_Major_Gene)),]$normalized_read_count))
|
|
|
138 locussum2 = append(locussum2, sum(patient2[(grepl(V_Segment, patient2$V_Segment_Major_Gene) & grepl(J_Segment, patient2$J_Segment_Major_Gene)),]$normalized_read_count))
|
|
0
|
139 #threshhold = 0
|
|
|
140 if(threshhold != 0){
|
|
|
141 if(sum(one) > 0){
|
|
15
|
142 dfOne = patient1[one,c("V_Segment_Major_Gene", "J_Segment_Major_Gene", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")]
|
|
|
143 colnames(dfOne) = c("Proximal segment", "Distal segment", "normalized_read_count", "Frequency", "Clone Sequence", "Related_to_leukemia_clone")
|
|
0
|
144 filenameOne = paste(oneSample, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
145 write.table(dfOne, file=paste(filenameOne, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
146 }
|
|
|
147 if(sum(two) > 0){
|
|
15
|
148 dfTwo = patient2[two,c("V_Segment_Major_Gene", "J_Segment_Major_Gene", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")]
|
|
|
149 colnames(dfTwo) = c("Proximal segment", "Distal segment", "normalized_read_count", "Frequency", "Clone Sequence", "Related_to_leukemia_clone")
|
|
0
|
150 filenameTwo = paste(twoSample, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
151 write.table(dfTwo, file=paste(filenameTwo, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
152 }
|
|
|
153 }
|
|
|
154 if(sum(both) > 0){
|
|
15
|
155 dfBoth = patientMerge[both,c("V_Segment_Major_Gene.x", "J_Segment_Major_Gene.x", "normalized_read_count.x", "Frequency.x", "Related_to_leukemia_clone.x", "Clone_Sequence.x", "V_Segment_Major_Gene.y", "J_Segment_Major_Gene.y", "normalized_read_count.y", "Frequency.y", "Related_to_leukemia_clone.y")]
|
|
|
156 colnames(dfBoth) = c(paste("Proximal segment", oneSample), paste("Distal segment", oneSample), paste("Normalized_Read_Count", oneSample), paste("Frequency", oneSample), paste("Related_to_leukemia_clone", oneSample),"Clone Sequence", paste("Proximal segment", twoSample), paste("Distal segment", twoSample), paste("Normalized_Read_Count", twoSample), paste("Frequency", twoSample), paste("Related_to_leukemia_clone", twoSample))
|
|
0
|
157 filenameBoth = paste(oneSample, "_", twoSample, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
158 write.table(dfBoth, file=paste(filenameBoth, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
159 }
|
|
|
160 }
|
|
2
|
161 patientResult = data.frame("Locus"=product$Titles, "J_Segment"=product$J_Segments, "V_Segment"=product$V_Segments, "cut_off_value"=paste(">", product$interval, sep=""), "Both"=resBoth, "tmp1"=res1, "read_count1" = round(read1Count), "tmp2"=res2, "read_count2"= round(read2Count), "Sum"=res1 + res2 + resBoth, "percentage" = round((resBoth/(res1 + res2 + resBoth)) * 100, digits=2), "Locus_sum1"=locussum1, "Locus_sum2"=locussum2)
|
|
0
|
162 if(sum(is.na(patientResult$percentage)) > 0){
|
|
|
163 patientResult[is.na(patientResult$percentage),]$percentage = 0
|
|
|
164 }
|
|
|
165 colnames(patientResult)[6] = oneSample
|
|
|
166 colnames(patientResult)[8] = twoSample
|
|
|
167 colnamesBak = colnames(patientResult)
|
|
2
|
168 colnames(patientResult) = c("Ig/TCR gene rearrangement type", "Distal Gene segment", "Proximal gene segment", "cut_off_value", paste("Number of sequences ", patient, "_Both", sep=""), paste("Number of sequences", oneSample, sep=""), paste("Normalized Read Count", oneSample), paste("Number of sequences", twoSample, sep=""), paste("Normalized Read Count", twoSample), paste("Sum number of sequences", patient), paste("Percentage of sequences ", patient, "_Both", sep=""), paste("Locus Sum", oneSample), paste("Locus Sum", twoSample))
|
|
0
|
169 write.table(patientResult, file=paste(patient, "_", onShort, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
170 colnames(patientResult) = colnamesBak
|
|
|
171
|
|
|
172 patientResult$Locus = factor(patientResult$Locus, Titles)
|
|
|
173 patientResult$cut_off_value = factor(patientResult$cut_off_value, paste(">", interval, sep=""))
|
|
|
174
|
|
|
175 plt = ggplot(patientResult[,c("Locus", "cut_off_value", "Both")])
|
|
|
176 plt = plt + geom_bar( aes( x=factor(cut_off_value), y=Both), stat='identity', position="dodge", fill="#79c36a")
|
|
|
177 plt = plt + facet_grid(.~Locus) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
|
|
178 plt = plt + geom_text(aes(ymax=max(Both), x=cut_off_value,y=Both,label=Both), angle=90, hjust=0)
|
|
|
179 plt = plt + xlab("Reads per locus") + ylab("Count") + ggtitle("Number of clones in both")
|
|
|
180 plt = plt + theme(plot.margin = unit(c(1,8.8,0.5,1.5), "lines"))
|
|
|
181 png(paste(patient, "_", onShort, ".png", sep=""), width=1920, height=1080)
|
|
|
182 print(plt)
|
|
|
183 dev.off()
|
|
|
184 #(t,r,b,l)
|
|
|
185 plt = ggplot(patientResult[,c("Locus", "cut_off_value", "percentage")])
|
|
|
186 plt = plt + geom_bar( aes( x=factor(cut_off_value), y=percentage), stat='identity', position="dodge", fill="#79c36a")
|
|
|
187 plt = plt + facet_grid(.~Locus) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
|
|
188 plt = plt + geom_text(aes(ymax=max(percentage), x=cut_off_value,y=percentage,label=percentage), angle=90, hjust=0)
|
|
|
189 plt = plt + xlab("Reads per locus") + ylab("Count") + ggtitle("% clones in both left and right")
|
|
|
190 plt = plt + theme(plot.margin = unit(c(1,8.8,0.5,1.5), "lines"))
|
|
|
191 png(paste(patient, "_percent_", onShort, ".png", sep=""), width=1920, height=1080)
|
|
|
192 print(plt)
|
|
|
193 dev.off()
|
|
|
194
|
|
|
195 patientResult = melt(patientResult[,c('Locus','cut_off_value', oneSample, twoSample)] ,id.vars=1:2)
|
|
|
196 patientResult$relativeValue = patientResult$value * 10
|
|
|
197 patientResult[patientResult$relativeValue == 0,]$relativeValue = 1
|
|
|
198 plt = ggplot(patientResult)
|
|
|
199 plt = plt + geom_bar( aes( x=factor(cut_off_value), y=relativeValue, fill=variable), stat='identity', position="dodge")
|
|
|
200 plt = plt + facet_grid(.~Locus) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
|
|
201 plt = plt + scale_y_continuous(trans="log", breaks=10^c(0:10), labels=c(0, 10^c(0:9)))
|
|
|
202 plt = plt + geom_text(data=patientResult[patientResult$variable == oneSample,], aes(ymax=max(value), x=cut_off_value,y=relativeValue,label=value), angle=90, position=position_dodge(width=0.9), hjust=0, vjust=-0.2)
|
|
|
203 plt = plt + geom_text(data=patientResult[patientResult$variable == twoSample,], aes(ymax=max(value), x=cut_off_value,y=relativeValue,label=value), angle=90, position=position_dodge(width=0.9), hjust=0, vjust=0.8)
|
|
|
204 plt = plt + xlab("Reads per locus") + ylab("Count") + ggtitle(paste("Number of clones in only ", oneSample, " and only ", twoSample, sep=""))
|
|
|
205 png(paste(patient, "_", onShort, "_both.png", sep=""), width=1920, height=1080)
|
|
|
206 print(plt)
|
|
|
207 dev.off()
|
|
|
208 }
|
|
|
209
|
|
3
|
210 cat("<tr><td>Starting Frequency analysis</td></tr>", file=logfile, append=T)
|
|
|
211
|
|
0
|
212 interval = intervalFreq
|
|
|
213 intervalOrder = data.frame("interval"=paste(">", interval, sep=""), "intervalOrder"=1:length(interval))
|
|
4
|
214 product = data.frame("Titles"=rep(Titles, each=length(interval)), "interval"=rep(interval, times=10), "V_Segments"=rep(V_Segments, each=length(interval)), "J_Segments"=rep(J_Segments, each=length(interval)))
|
|
|
215 mclapply(patients, FUN=patientCountOnColumn, product = product, interval=interval, on="Frequency", appendtxt=T)
|
|
0
|
216
|
|
3
|
217 cat("<tr><td>Starting Cell Count analysis</td></tr>", file=logfile, append=T)
|
|
|
218
|
|
0
|
219 interval = intervalReads
|
|
|
220 intervalOrder = data.frame("interval"=paste(">", interval, sep=""), "intervalOrder"=1:length(interval))
|
|
4
|
221 product = data.frame("Titles"=rep(Titles, each=length(interval)), "interval"=rep(interval, times=10), "V_Segments"=rep(V_Segments, each=length(interval)), "J_Segments"=rep(J_Segments, each=length(interval)))
|
|
9
|
222 mclapply(patients, FUN=patientCountOnColumn, product = product, interval=interval, on="normalized_read_count")
|
|
0
|
223
|
|
3
|
224 cat("</table></html>", file=logfile, append=T)
|
|
|
225
|
|
7
|
226
|
|
13
|
227
|
|
7
|
228 tripletAnalysis <- function(patient1, label1, patient2, label2, patient3, label3, product, interval, on, appendTriplets= FALSE){
|
|
|
229 onShort = "reads"
|
|
|
230 if(on == "Frequency"){
|
|
|
231 onShort = "freq"
|
|
|
232 }
|
|
18
|
233 onx = paste(on, ".x", sep="")
|
|
|
234 ony = paste(on, ".y", sep="")
|
|
|
235 onz = paste(on, ".z", sep="")
|
|
7
|
236 type="triplet"
|
|
|
237
|
|
|
238 threshholdIndex = which(colnames(product) == "interval")
|
|
|
239 V_SegmentIndex = which(colnames(product) == "V_Segments")
|
|
|
240 J_SegmentIndex = which(colnames(product) == "J_Segments")
|
|
|
241 titleIndex = which(colnames(product) == "Titles")
|
|
|
242 sampleIndex = which(colnames(patient1) == "Sample")
|
|
|
243 patientIndex = which(colnames(patient1) == "Patient")
|
|
|
244 oneSample = paste(patient1[1,sampleIndex], sep="")
|
|
|
245 twoSample = paste(patient2[1,sampleIndex], sep="")
|
|
|
246 threeSample = paste(patient3[1,sampleIndex], sep="")
|
|
|
247
|
|
12
|
248 #patient1$merge = paste(patient1$V_Segment_Major_Gene, patient1$J_Segment_Major_Gene, patient1$CDR3_Sense_Sequence)
|
|
|
249 #patient2$merge = paste(patient2$V_Segment_Major_Gene, patient2$J_Segment_Major_Gene, patient2$CDR3_Sense_Sequence)
|
|
|
250 #patient3$merge = paste(patient3$V_Segment_Major_Gene, patient3$J_Segment_Major_Gene, patient3$CDR3_Sense_Sequence)
|
|
|
251
|
|
15
|
252 patient1$merge = paste(patient1$Clone_Sequence)
|
|
|
253 patient2$merge = paste(patient2$Clone_Sequence)
|
|
|
254 patient3$merge = paste(patient3$Clone_Sequence)
|
|
9
|
255
|
|
|
256 patientMerge = merge(patient1, patient2, by="merge")
|
|
|
257 patientMerge = merge(patientMerge, patient3, by="merge")
|
|
13
|
258 colnames(patientMerge)[30:length(colnames(patientMerge))] = paste(colnames(patientMerge)[30:length(colnames(patientMerge))], ".z", sep="")
|
|
18
|
259 patientMerge$thresholdValue = pmax(patientMerge[,onx], patientMerge[,ony], patientMerge[,onz])
|
|
20
|
260
|
|
|
261 patientMerge12 = merge(patient1, patient2, by="merge")
|
|
|
262 patientMerge12$thresholdValue = pmax(patientMerge12[,onx], patientMerge12[,ony])
|
|
|
263 patientMerge13 = merge(patient1, patient3, by="merge")
|
|
|
264 patientMerge13$thresholdValue = pmax(patientMerge13[,onx], patientMerge13[,ony])
|
|
|
265 patientMerge23 = merge(patient2, patient3, by="merge")
|
|
|
266 patientMerge23$thresholdValue = pmax(patientMerge23[,onx], patientMerge23[,ony])
|
|
|
267
|
|
24
|
268 scatterplot_data_columns = c("Clone_Sequence", "Frequency", "normalized_read_count", "V_Segment_Major_Gene", "J_Segment_Major_Gene")
|
|
20
|
269 scatterplot_data = rbind(patient1[,scatterplot_data_columns], patient2[,scatterplot_data_columns], patient3[,scatterplot_data_columns])
|
|
|
270 scatterplot_data = scatterplot_data[!duplicated(scatterplot_data$Clone_Sequence),]
|
|
27
|
271 scatterplot_data$type = factor(x="In one", levels=c("In one", "In two", "In three", "In multiple"))
|
|
20
|
272
|
|
7
|
273 res1 = vector()
|
|
|
274 res2 = vector()
|
|
|
275 res3 = vector()
|
|
20
|
276 res12 = vector()
|
|
|
277 res13 = vector()
|
|
|
278 res23 = vector()
|
|
7
|
279 resAll = vector()
|
|
|
280 read1Count = vector()
|
|
|
281 read2Count = vector()
|
|
|
282 read3Count = vector()
|
|
|
283
|
|
|
284 if(appendTriplets){
|
|
9
|
285 cat(paste(label1, label2, label3, sep="\t"), file="triplets.txt", append=T, sep="", fill=3)
|
|
7
|
286 }
|
|
|
287 for(iter in 1:length(product[,1])){
|
|
|
288 threshhold = product[iter,threshholdIndex]
|
|
|
289 V_Segment = paste(".*", as.character(product[iter,V_SegmentIndex]), ".*", sep="")
|
|
|
290 J_Segment = paste(".*", as.character(product[iter,J_SegmentIndex]), ".*", sep="")
|
|
18
|
291 #all = (grepl(V_Segment, patientMerge$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge$J_Segment_Major_Gene.x) & patientMerge[,onx] > threshhold & patientMerge[,ony] > threshhold & patientMerge[,onz] > threshhold)
|
|
|
292 all = (grepl(V_Segment, patientMerge$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge$J_Segment_Major_Gene.x) & patientMerge$thresholdValue > threshhold)
|
|
7
|
293
|
|
25
|
294 one_two = (grepl(V_Segment, patientMerge12$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge12$J_Segment_Major_Gene.x) & patientMerge12$thresholdValue > threshhold & !(patientMerge12$Clone_Sequence.x %in% patientMerge[all,]$merge))
|
|
|
295 one_three = (grepl(V_Segment, patientMerge13$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge13$J_Segment_Major_Gene.x) & patientMerge13$thresholdValue > threshhold & !(patientMerge13$Clone_Sequence.x %in% patientMerge[all,]$merge))
|
|
|
296 two_three = (grepl(V_Segment, patientMerge23$V_Segment_Major_Gene.x) & grepl(J_Segment, patientMerge23$J_Segment_Major_Gene.x) & patientMerge23$thresholdValue > threshhold & !(patientMerge23$Clone_Sequence.x %in% patientMerge[all,]$merge))
|
|
24
|
297
|
|
25
|
298 one = (grepl(V_Segment, patient1$V_Segment_Major_Gene) & grepl(J_Segment, patient1$J_Segment_Major_Gene) & patient1[,on] > threshhold & !(patient1$Clone_Sequence %in% patientMerge[all,]$merge) & !(patient1$Clone_Sequence %in% patientMerge12[one_two,]$merge) & !(patient1$Clone_Sequence %in% patientMerge13[one_three,]$merge))
|
|
|
299 two = (grepl(V_Segment, patient2$V_Segment_Major_Gene) & grepl(J_Segment, patient2$J_Segment_Major_Gene) & patient2[,on] > threshhold & !(patient2$Clone_Sequence %in% patientMerge[all,]$merge) & !(patient2$Clone_Sequence %in% patientMerge12[one_two,]$merge) & !(patient2$Clone_Sequence %in% patientMerge23[two_three,]$merge))
|
|
|
300 three = (grepl(V_Segment, patient3$V_Segment_Major_Gene) & grepl(J_Segment, patient3$J_Segment_Major_Gene) & patient3[,on] > threshhold & !(patient3$Clone_Sequence %in% patientMerge[all,]$merge) & !(patient3$Clone_Sequence %in% patientMerge13[one_three,]$merge) & !(patient3$Clone_Sequence %in% patientMerge23[two_three,]$merge))
|
|
20
|
301
|
|
18
|
302 read1Count = append(read1Count, sum(patient1[one,]$normalized_read_count) + sum(patientMerge[all,]$normalized_read_count.x))
|
|
|
303 read2Count = append(read2Count, sum(patient2[two,]$normalized_read_count) + sum(patientMerge[all,]$normalized_read_count.y))
|
|
|
304 read3Count = append(read3Count, sum(patient3[three,]$normalized_read_count) + sum(patientMerge[all,]$normalized_read_count.z))
|
|
7
|
305 res1 = append(res1, sum(one))
|
|
|
306 res2 = append(res2, sum(two))
|
|
|
307 res3 = append(res3, sum(three))
|
|
|
308 resAll = append(resAll, sum(all))
|
|
20
|
309 res12 = append(res12, sum(one_two))
|
|
|
310 res13 = append(res13, sum(one_three))
|
|
|
311 res23 = append(res23, sum(two_three))
|
|
7
|
312 #threshhold = 0
|
|
|
313 if(threshhold != 0){
|
|
|
314 if(sum(one) > 0){
|
|
20
|
315 dfOne = patient1[one,c("V_Segment_Major_Gene", "J_Segment_Major_Gene", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")]
|
|
|
316 colnames(dfOne) = c("Proximal segment", "Distal segment", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")
|
|
7
|
317 filenameOne = paste(label1, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
318 write.table(dfOne, file=paste(filenameOne, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
319 }
|
|
|
320 if(sum(two) > 0){
|
|
20
|
321 dfTwo = patient2[two,c("V_Segment_Major_Gene", "J_Segment_Major_Gene", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")]
|
|
|
322 colnames(dfTwo) = c("Proximal segment", "Distal segment", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")
|
|
7
|
323 filenameTwo = paste(label2, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
324 write.table(dfTwo, file=paste(filenameTwo, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
325 }
|
|
|
326 if(sum(three) > 0){
|
|
20
|
327 dfThree = patient3[three,c("V_Segment_Major_Gene", "J_Segment_Major_Gene", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")]
|
|
|
328 colnames(dfThree) = c("Proximal segment", "Distal segment", "normalized_read_count", "Frequency", "Clone_Sequence", "Related_to_leukemia_clone")
|
|
7
|
329 filenameThree = paste(label3, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
330 write.table(dfThree, file=paste(filenameThree, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
331 }
|
|
20
|
332 if(sum(one_two) > 0){
|
|
|
333 dfOne_two = patientMerge12[one_two,c("V_Segment_Major_Gene.x", "J_Segment_Major_Gene.x", "normalized_read_count.x", "Frequency.x", "Related_to_leukemia_clone.x", "Clone_Sequence.x", "V_Segment_Major_Gene.y", "J_Segment_Major_Gene.y", "normalized_read_count.y", "Frequency.y", "Related_to_leukemia_clone.y")]
|
|
|
334 colnames(dfOne_two) = c(paste("Proximal segment", oneSample), paste("Distal segment", oneSample), paste("Normalized_Read_Count", oneSample), paste("Frequency", oneSample), paste("Related_to_leukemia_clone", oneSample),"Clone_Sequence", paste("Proximal segment", twoSample), paste("Distal segment", twoSample), paste("Normalized_Read_Count", twoSample), paste("Frequency", twoSample), paste("Related_to_leukemia_clone", twoSample))
|
|
|
335 filenameOne_two = paste(label1, "_", label2, "_", product[iter, titleIndex], "_", threshhold, onShort, sep="")
|
|
|
336 write.table(dfOne_two, file=paste(filenameOne_two, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
337 }
|
|
|
338 if(sum(one_three) > 0){
|
|
|
339 dfOne_three = patientMerge13[one_three,c("V_Segment_Major_Gene.x", "J_Segment_Major_Gene.x", "normalized_read_count.x", "Frequency.x", "Related_to_leukemia_clone.x", "Clone_Sequence.x", "V_Segment_Major_Gene.y", "J_Segment_Major_Gene.y", "normalized_read_count.y", "Frequency.y", "Related_to_leukemia_clone.y")]
|
|
|
340 colnames(dfOne_three) = c(paste("Proximal segment", oneSample), paste("Distal segment", oneSample), paste("Normalized_Read_Count", oneSample), paste("Frequency", oneSample), paste("Related_to_leukemia_clone", oneSample),"Clone_Sequence", paste("Proximal segment", threeSample), paste("Distal segment", threeSample), paste("Normalized_Read_Count", threeSample), paste("Frequency", threeSample), paste("Related_to_leukemia_clone", threeSample))
|
|
|
341 filenameOne_three = paste(label1, "_", label3, "_", product[iter, titleIndex], "_", threshhold, onShort, sep="")
|
|
|
342 write.table(dfOne_three, file=paste(filenameOne_three, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
343 }
|
|
|
344 if(sum(two_three) > 0){
|
|
|
345 dfTwo_three = patientMerge23[two_three,c("V_Segment_Major_Gene.x", "J_Segment_Major_Gene.x", "normalized_read_count.x", "Frequency.x", "Related_to_leukemia_clone.x", "Clone_Sequence.x", "V_Segment_Major_Gene.y", "J_Segment_Major_Gene.y", "normalized_read_count.y", "Frequency.y", "Related_to_leukemia_clone.y")]
|
|
|
346 colnames(dfTwo_three) = c(paste("Proximal segment", twoSample), paste("Distal segment", twoSample), paste("Normalized_Read_Count", twoSample), paste("Frequency", twoSample), paste("Related_to_leukemia_clone", twoSample),"Clone_Sequence", paste("Proximal segment", threeSample), paste("Distal segment", threeSample), paste("Normalized_Read_Count", threeSample), paste("Frequency", threeSample), paste("Related_to_leukemia_clone", threeSample))
|
|
|
347 filenameTwo_three = paste(label2, "_", label3, "_", product[iter, titleIndex], "_", threshhold, onShort, sep="")
|
|
|
348 write.table(dfTwo_three, file=paste(filenameTwo_three, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
349 }
|
|
|
350 } else { #scatterplot data
|
|
24
|
351 scatterplot_locus_data = scatterplot_data[grepl(V_Segment, scatterplot_data$V_Segment_Major_Gene) & grepl(J_Segment, scatterplot_data$J_Segment_Major_Gene),]
|
|
27
|
352 in_two = (scatterplot_locus_data$Clone_Sequence %in% patientMerge12[one_two,]$Clone_Sequence.x) | (scatterplot_locus_data$Clone_Sequence %in% patientMerge13[one_three,]$Clone_Sequence.x) | (scatterplot_locus_data$Clone_Sequence %in% patientMerge23[two_three,]$Clone_Sequence.x)
|
|
|
353 if(sum(in_two) > 0){
|
|
|
354 scatterplot_locus_data[in_two,]$type = "In two"
|
|
|
355 }
|
|
|
356 in_three = (scatterplot_locus_data$Clone_Sequence %in% patientMerge[all,]$Clone_Sequence.x)
|
|
|
357 if(sum(in_three)> 0){
|
|
|
358 scatterplot_locus_data[in_three,]$type = "In three"
|
|
|
359 }
|
|
|
360 not_in_one = scatterplot_locus_data$type != "In one"
|
|
|
361 print(not_in_one)
|
|
|
362 if(sum(not_in_one) > 0){
|
|
|
363 scatterplot_locus_data[not_in_one,]$type = "In multiple"
|
|
|
364 }
|
|
20
|
365 p = NULL
|
|
|
366 if(nrow(scatterplot_locus_data) != 0){
|
|
|
367 if(on == "normalized_read_count"){
|
|
|
368 scales = 10^(0:ceiling(log10(max(scatterplot_locus_data$normalized_read_count))))
|
|
|
369 p = ggplot(scatterplot_locus_data, aes(type, normalized_read_count)) + scale_y_log10(breaks=scales,labels=scales)
|
|
|
370 } else {
|
|
|
371 p = ggplot(scatterplot_locus_data, aes(type, Frequency))
|
|
|
372 }
|
|
|
373 p = p + geom_point(aes(colour=type), position="jitter")
|
|
25
|
374 p = p + xlab("In one or in multiple samples") + ylab(onShort) + ggtitle(paste(label1, label2, label3, onShort, product[iter, titleIndex]))
|
|
20
|
375 } else {
|
|
|
376 p = ggplot(NULL, aes(x=c("In one", "In multiple"),y=0)) + geom_blank(NULL) + xlab("In two or in three of the samples") + ylab(onShort) + ggtitle(paste(label1, label2, label3, onShort, product[iter, titleIndex]))
|
|
|
377 }
|
|
|
378 png(paste(label1, "_", label2, "_", label3, "_", onShort, "_", product[iter, titleIndex],"_scatter.png", sep=""))
|
|
|
379 print(p)
|
|
|
380 dev.off()
|
|
|
381 }
|
|
7
|
382 if(sum(all) > 0){
|
|
20
|
383 dfAll = patientMerge[all,c("V_Segment_Major_Gene.x", "J_Segment_Major_Gene.x", "normalized_read_count.x", "Frequency.x", "Related_to_leukemia_clone.x", "Clone_Sequence.x", "V_Segment_Major_Gene.y", "J_Segment_Major_Gene.y", "normalized_read_count.y", "Frequency.y", "Related_to_leukemia_clone.y", "V_Segment_Major_Gene.z", "J_Segment_Major_Gene.z", "normalized_read_count.z", "Frequency.z", "Related_to_leukemia_clone.z")]
|
|
|
384 colnames(dfAll) = c(paste("Proximal segment", oneSample), paste("Distal segment", oneSample), paste("Normalized_Read_Count", oneSample), paste("Frequency", oneSample), paste("Related_to_leukemia_clone", oneSample),"Clone_Sequence", paste("Proximal segment", twoSample), paste("Distal segment", twoSample), paste("Normalized_Read_Count", twoSample), paste("Frequency", twoSample), paste("Related_to_leukemia_clone", twoSample), paste("Proximal segment", threeSample), paste("Distal segment", threeSample), paste("Normalized_Read_Count", threeSample), paste("Frequency", threeSample), paste("Related_to_leukemia_clone", threeSample))
|
|
7
|
385 filenameAll = paste(label1, "_", label2, "_", label3, "_", product[iter, titleIndex], "_", threshhold, sep="")
|
|
|
386 write.table(dfAll, file=paste(filenameAll, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
387 }
|
|
|
388 }
|
|
20
|
389 #patientResult = data.frame("Locus"=product$Titles, "J_Segment"=product$J_Segments, "V_Segment"=product$V_Segments, "cut_off_value"=paste(">", product$interval, sep=""), "All"=resAll, "tmp1"=res1, "read_count1" = round(read1Count), "tmp2"=res2, "read_count2"= round(read2Count), "tmp3"=res3, "read_count3"=round(read3Count))
|
|
|
390 patientResult = data.frame("Locus"=product$Titles, "J_Segment"=product$J_Segments, "V_Segment"=product$V_Segments, "cut_off_value"=paste(">", product$interval, sep=""), "All"=resAll, "tmp1"=res1, "tmp2"=res2, "tmp3"=res3, "tmp12"=res12, "tmp13"=res13, "tmp23"=res23)
|
|
7
|
391 colnames(patientResult)[6] = oneSample
|
|
20
|
392 colnames(patientResult)[7] = twoSample
|
|
|
393 colnames(patientResult)[8] = threeSample
|
|
|
394 colnames(patientResult)[9] = paste(oneSample, twoSample, sep="_")
|
|
|
395 colnames(patientResult)[10] = paste(oneSample, twoSample, sep="_")
|
|
|
396 colnames(patientResult)[11] = paste(oneSample, twoSample, sep="_")
|
|
7
|
397
|
|
|
398 colnamesBak = colnames(patientResult)
|
|
20
|
399 colnames(patientResult) = c("Ig/TCR gene rearrangement type", "Distal Gene segment", "Proximal gene segment", "cut_off_value", "Number of sequences All", paste("Number of sequences", oneSample), paste("Number of sequences", twoSample), paste("Number of sequences", threeSample), paste("Number of sequences", oneSample, twoSample), paste("Number of sequences", oneSample, threeSample), paste("Number of sequences", twoSample, threeSample))
|
|
7
|
400 write.table(patientResult, file=paste(label1, "_", label2, "_", label3, "_", onShort, ".txt", sep=""), quote=F, sep="\t", dec=",", row.names=F, col.names=T)
|
|
|
401 colnames(patientResult) = colnamesBak
|
|
|
402
|
|
|
403 patientResult$Locus = factor(patientResult$Locus, Titles)
|
|
|
404 patientResult$cut_off_value = factor(patientResult$cut_off_value, paste(">", interval, sep=""))
|
|
|
405
|
|
|
406 plt = ggplot(patientResult[,c("Locus", "cut_off_value", "All")])
|
|
|
407 plt = plt + geom_bar( aes( x=factor(cut_off_value), y=All), stat='identity', position="dodge", fill="#79c36a")
|
|
|
408 plt = plt + facet_grid(.~Locus) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
|
|
409 plt = plt + geom_text(aes(ymax=max(All), x=cut_off_value,y=All,label=All), angle=90, hjust=0)
|
|
|
410 plt = plt + xlab("Reads per locus") + ylab("Count") + ggtitle("Number of clones in All")
|
|
|
411 plt = plt + theme(plot.margin = unit(c(1,8.8,0.5,1.5), "lines"))
|
|
|
412 png(paste(label1, "_", label2, "_", label3, "_", onShort, "_total_all.png", sep=""), width=1920, height=1080)
|
|
|
413 print(plt)
|
|
|
414 dev.off()
|
|
|
415
|
|
|
416 fontSize = 4
|
|
|
417
|
|
|
418 bak = patientResult
|
|
|
419 patientResult = melt(patientResult[,c('Locus','cut_off_value', oneSample, twoSample, threeSample)] ,id.vars=1:2)
|
|
|
420 patientResult$relativeValue = patientResult$value * 10
|
|
|
421 patientResult[patientResult$relativeValue == 0,]$relativeValue = 1
|
|
|
422 plt = ggplot(patientResult)
|
|
|
423 plt = plt + geom_bar( aes( x=factor(cut_off_value), y=relativeValue, fill=variable), stat='identity', position="dodge")
|
|
|
424 plt = plt + facet_grid(.~Locus) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
|
|
|
425 plt = plt + scale_y_continuous(trans="log", breaks=10^c(0:10), labels=c(0, 10^c(0:9)))
|
|
|
426 plt = plt + geom_text(data=patientResult[patientResult$variable == oneSample,], aes(ymax=max(value), x=cut_off_value,y=relativeValue,label=value), angle=90, position=position_dodge(width=0.9), hjust=0, vjust=-0.7, size=fontSize)
|
|
|
427 plt = plt + geom_text(data=patientResult[patientResult$variable == twoSample,], aes(ymax=max(value), x=cut_off_value,y=relativeValue,label=value), angle=90, position=position_dodge(width=0.9), hjust=0, vjust=0.4, size=fontSize)
|
|
|
428 plt = plt + geom_text(data=patientResult[patientResult$variable == threeSample,], aes(ymax=max(value), x=cut_off_value,y=relativeValue,label=value), angle=90, position=position_dodge(width=0.9), hjust=0, vjust=1.5, size=fontSize)
|
|
|
429 plt = plt + xlab("Reads per locus") + ylab("Count") + ggtitle("Number of clones in only one sample")
|
|
|
430 png(paste(label1, "_", label2, "_", label3, "_", onShort, "_indiv_all.png", sep=""), width=1920, height=1080)
|
|
|
431 print(plt)
|
|
|
432 dev.off()
|
|
|
433 }
|
|
|
434
|
|
9
|
435 triplets$uniqueID = "ID"
|
|
|
436
|
|
|
437 triplets[grepl("16278_Left", triplets$Sample),]$uniqueID = "16278_26402_26759_Left"
|
|
|
438 triplets[grepl("26402_Left", triplets$Sample),]$uniqueID = "16278_26402_26759_Left"
|
|
|
439 triplets[grepl("26759_Left", triplets$Sample),]$uniqueID = "16278_26402_26759_Left"
|
|
|
440
|
|
|
441 triplets[grepl("16278_Right", triplets$Sample),]$uniqueID = "16278_26402_26759_Right"
|
|
|
442 triplets[grepl("26402_Right", triplets$Sample),]$uniqueID = "16278_26402_26759_Right"
|
|
|
443 triplets[grepl("26759_Right", triplets$Sample),]$uniqueID = "16278_26402_26759_Right"
|
|
|
444
|
|
|
445 triplets[grepl("14696", triplets$Patient),]$uniqueID = "14696"
|
|
|
446
|
|
13
|
447 triplets$locus_V = substring(triplets$V_Segment_Major_Gene, 0, 4)
|
|
|
448 triplets$locus_J = substring(triplets$J_Segment_Major_Gene, 0, 4)
|
|
|
449 min_cell_count = data.frame(data.table(triplets)[, list(min_cell_count=min(.SD$Cell_Count)), by=c("uniqueID", "locus_V", "locus_J")])
|
|
|
450
|
|
|
451 triplets$min_cell_paste = paste(triplets$uniqueID, triplets$locus_V, triplets$locus_J)
|
|
|
452 min_cell_count$min_cell_paste = paste(min_cell_count$uniqueID, min_cell_count$locus_V, min_cell_count$locus_J)
|
|
|
453
|
|
|
454 min_cell_count = min_cell_count[,c("min_cell_paste", "min_cell_count")]
|
|
9
|
455
|
|
13
|
456 triplets = merge(triplets, min_cell_count, by="min_cell_paste")
|
|
|
457
|
|
|
458 triplets$normalized_read_count = round(triplets$Clone_Molecule_Count_From_Spikes / triplets$Cell_Count * triplets$min_cell_count / 2, digits=2) #??????????????????????????????????? wel of geen / 2
|
|
|
459
|
|
|
460 triplets = triplets[triplets$normalized_read_count >= min_cells,]
|
|
|
461
|
|
|
462 column_drops = c("locus_V", "locus_J", "min_cell_count", "min_cell_paste")
|
|
|
463
|
|
|
464 triplets = triplets[,!(colnames(triplets) %in% column_drops)]
|
|
9
|
465
|
|
7
|
466 interval = intervalReads
|
|
|
467 intervalOrder = data.frame("interval"=paste(">", interval, sep=""), "intervalOrder"=1:length(interval))
|
|
|
468 product = data.frame("Titles"=rep(Titles, each=length(interval)), "interval"=rep(interval, times=10), "V_Segments"=rep(V_Segments, each=length(interval)), "J_Segments"=rep(J_Segments, each=length(interval)))
|
|
|
469
|
|
9
|
470 one = triplets[triplets$Sample == "14696_reg_BM",]
|
|
|
471 two = triplets[triplets$Sample == "24536_reg_BM",]
|
|
|
472 three = triplets[triplets$Sample == "24062_reg_BM",]
|
|
8
|
473 tripletAnalysis(one, "14696_1", two, "14696_2", three, "14696_3", product=product, interval=interval, on="normalized_read_count", T)
|
|
7
|
474
|
|
9
|
475 one = triplets[triplets$Sample == "16278_Left",]
|
|
|
476 two = triplets[triplets$Sample == "26402_Left",]
|
|
|
477 three = triplets[triplets$Sample == "26759_Left",]
|
|
8
|
478 tripletAnalysis(one, "16278_Left", two, "26402_Left", three, "26759_Left", product=product, interval=interval, on="normalized_read_count", T)
|
|
7
|
479
|
|
9
|
480 one = triplets[triplets$Sample == "16278_Right",]
|
|
|
481 two = triplets[triplets$Sample == "26402_Right",]
|
|
|
482 three = triplets[triplets$Sample == "26759_Right",]
|
|
8
|
483 tripletAnalysis(one, "16278_Right", two, "26402_Right", three, "26759_Right", product=product, interval=interval, on="normalized_read_count", T)
|
|
7
|
484
|
|
|
485
|
|
|
486 interval = intervalFreq
|
|
|
487 intervalOrder = data.frame("interval"=paste(">", interval, sep=""), "intervalOrder"=1:length(interval))
|
|
|
488 product = data.frame("Titles"=rep(Titles, each=length(interval)), "interval"=rep(interval, times=10), "V_Segments"=rep(V_Segments, each=length(interval)), "J_Segments"=rep(J_Segments, each=length(interval)))
|
|
|
489
|
|
9
|
490 one = triplets[triplets$Sample == "14696_reg_BM",]
|
|
|
491 two = triplets[triplets$Sample == "24536_reg_BM",]
|
|
|
492 three = triplets[triplets$Sample == "24062_reg_BM",]
|
|
8
|
493 tripletAnalysis(one, "14696_1", two, "14696_2", three, "14696_3", product=product, interval=interval, on="Frequency", F)
|
|
7
|
494
|
|
9
|
495 one = triplets[triplets$Sample == "16278_Left",]
|
|
|
496 two = triplets[triplets$Sample == "26402_Left",]
|
|
|
497 three = triplets[triplets$Sample == "26759_Left",]
|
|
8
|
498 tripletAnalysis(one, "16278_Left", two, "26402_Left", three, "26759_Left", product=product, interval=interval, on="Frequency", F)
|
|
7
|
499
|
|
9
|
500 one = triplets[triplets$Sample == "16278_Right",]
|
|
|
501 two = triplets[triplets$Sample == "26402_Right",]
|
|
|
502 three = triplets[triplets$Sample == "26759_Right",]
|
|
8
|
503 tripletAnalysis(one, "16278_Right", two, "26402_Right", three, "26759_Right", product=product, interval=interval, on="Frequency", F)
|
