annotate Contra/scripts/cn_analysis.v4.R @ 15:f4345d10e1ad

Uploaded
author fcaramia
date Tue, 11 Dec 2012 18:52:28 -0500
parents 7564f3b1e675
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
0
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
1 # ----------------------------------------------------------------------#
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
2 # Copyright (c) 2011, Richard Lupat & Jason Li.
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
3 #
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
4 # > Source License <
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
5 # This file is part of CONTRA.
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
6 #
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
7 # CONTRA is free software: you can redistribute it and/or modify
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
8 # it under the terms of the GNU General Public License as published by
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
9 # the Free Software Foundation, either version 3 of the License, or
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
10 # (at your option) any later version.
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
11 #
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
12 # CONTRA is distributed in the hope that it will be useful,
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
13 # but WITHOUT ANY WARRANTY; without even the implied warranty of
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
14 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
15 # GNU General Public License for more details.
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
16 #
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
17 # You should have received a copy of the GNU General Public License
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
18 # along with CONTRA. If not, see <http://www.gnu.org/licenses/>.
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
19 #
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
20 #
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
21 #-----------------------------------------------------------------------#
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
22 # Last Updated : 30 Sept 2011 17:00PM
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
23
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
24
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
25 # Parameters Parsing (from Command Line)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
26 options <- commandArgs(trailingOnly = T)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
27 bins = as.numeric(options[1])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
28 rd.cutoff = as.numeric(options[2])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
29 min.bases = as.numeric(options[3])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
30 outf = options[4]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
31 sample.name = options[5]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
32 plotoption = options[6]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
33 actual.bin = as.numeric(options[7])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
34 min_normal_rd_for_call = as.numeric(options[8])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
35 min_tumour_rd_for_call = as.numeric(options[9])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
36 min_avg_cov_for_call = as.numeric(options[10])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
37
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
38 if (sample.name == "No-SampleName")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
39 sample.name = ""
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
40
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
41 if (sample.name != "")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
42 sample.name = paste(sample.name, ".", sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
43
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
44 # Setup output name
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
45 out.f = paste(outf, "/table/", sample.name, "CNATable.", rd.cutoff,"rd.", min.bases,"bases.", bins,"bins.txt", sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
46 pdf.out.f = paste(outf, "/plot/", sample.name, "densityplot.", bins, "bins.pdf", sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
47
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
48 # Open and read input files
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
49 # cnAverageFile = paste("bin", bins, ".txt", sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
50 cnAverageFile = paste(outf,"/buf/bin",bins,".txt",sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
51 boundariesFile = paste(outf,"/buf/bin",bins,".boundaries.txt",sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
52 print (cnAverageFile)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
53 cn.average = read.delim(cnAverageFile, as.is=F, header=F)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
54 cn.boundary= read.delim(boundariesFile,as.is=F, header=F)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
55
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
56 # Apply thresholds and data grouping
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
57 cn.average.aboveTs = cn.average[cn.average$V3>min.bases,]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
58 cn.average.list = as.matrix(cn.average.aboveTs$V4)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
59
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
60 # Get the mean and sd for each bins
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
61 cn.average.mean = c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
62 cn.average.sd = c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
63 cn.average.log= c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
64
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
65 # Density Plots for each bins
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
66 if (plotoption == "True"){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
67 pdf(pdf.out.f)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
68 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
69 for (j in 1:actual.bin){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
70 cn.average.nth = as.matrix(cn.average.aboveTs[cn.average.aboveTs$V15==j,]$V4)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
71 cn.coverage.nth = as.matrix(cn.average.aboveTs[cn.average.aboveTs$V15==j,]$V11)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
72 boundary.end = cn.boundary[cn.boundary$V1==j,]$V2
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
73 boundary.start = cn.boundary[cn.boundary$V1==(j-1),]$V2
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
74 boundary.mid = (boundary.end+boundary.start)/2
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
75 if (plotoption == "True") {
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
76 plot_title = paste("density: bin", bins, sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
77 #plot(density(cn.average.nth),xlim=c(-5,5), title=plot_title)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
78 plot(density(cn.average.nth),xlim=c(-5,5))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
79 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
80 cn.average.mean = c(cn.average.mean, mean(cn.average.nth))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
81 # cn.average.sd = c(cn.average.sd, sd(cn.average.nth))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
82 cn.average.sd = c(cn.average.sd, apply(cn.average.nth,2,sd))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
83 #cn.average.log = c(cn.average.log, boundary.mid)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
84 cn.average.log = c(cn.average.log, log(mean(cn.coverage.nth),2))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
85 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
86 if (plotoption == "True"){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
87 dev.off()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
88 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
89
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
90 # Put the data's details into matrices
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
91 ids = as.matrix(cn.average.aboveTs$V1)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
92 exons = as.matrix(cn.average.aboveTs$V6)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
93 exons.pos = as.matrix(cn.average.aboveTs$V5)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
94 gs = as.matrix(cn.average.aboveTs$V2)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
95 number.bases = as.matrix(cn.average.aboveTs$V3)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
96 mean = as.matrix(cn.average.aboveTs$V4)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
97 sd = as.matrix(cn.average.aboveTs$V7)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
98 tumour.rd = as.matrix(cn.average.aboveTs$V8)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
99 tumour.rd.ori = as.matrix(cn.average.aboveTs$V10)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
100 normal.rd = as.matrix(cn.average.aboveTs$V9)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
101 normal.rd.ori = as.matrix(cn.average.aboveTs$V11)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
102 median = as.matrix(cn.average.aboveTs$V12)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
103 MinLogRatio = as.matrix(cn.average.aboveTs$V13)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
104 MaxLogRatio = as.matrix(cn.average.aboveTs$V14)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
105 Bin = as.matrix(cn.average.aboveTs$V15)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
106 Chr = as.matrix(cn.average.aboveTs$V16)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
107 OriStCoordinate = as.matrix(cn.average.aboveTs$V17)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
108 OriEndCoordinate= as.matrix(cn.average.aboveTs$V18)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
109
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
110 # Linear Fit
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
111 logratios.mean = mean
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
112 logcov.mean = log2((normal.rd + tumour.rd)/2)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
113 fit.mean = lm(logratios.mean ~ logcov.mean)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
114 fit.x = fit.mean$coefficient[1]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
115 fit.y = fit.mean$coefficient[2]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
116
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
117 adjusted.lr = rep(NA, length(logratios.mean))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
118 for (j in 1:length(logratios.mean)){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
119 fitted.mean = fit.x + fit.y * logcov.mean[j]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
120 adjusted.lr[j] = logratios.mean[j] - fitted.mean
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
121 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
122
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
123 fit.mean2 = lm(adjusted.lr ~ logcov.mean)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
124 fit.mean.a = fit.mean2$coefficient[1]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
125 fit.mean.b = fit.mean2$coefficient[2]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
126
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
127 fit.mean.fn <- function(x, fit.a, fit.b){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
128 result = fit.a + fit.b * x
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
129 return (result)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
130 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
131
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
132 # Adjust SD based on the new adjusted log ratios
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
133 logratios.sd = c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
134 logcov.bins.mean= c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
135 for (j in 1:actual.bin){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
136 lr.bins.mean = as.matrix(adjusted.lr[cn.average.aboveTs$V15==j])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
137 # logratios.sd = c(logratios.sd, sd(lr.bins.mean))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
138 logratios.sd = c(logratios.sd, apply(lr.bins.mean,2,sd))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
139
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
140 cn.coverage.tumour.nth = as.matrix(cn.average.aboveTs[cn.average.aboveTs$V15==j,]$V8)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
141 cn.coverage.normal.nth = as.matrix(cn.average.aboveTs[cn.average.aboveTs$V15==j,]$V9)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
142 cn.coverage.nth = (cn.coverage.tumour.nth + cn.coverage.normal.nth) /2
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
143 logcov.bins.mean= c(logcov.bins.mean, log2(mean(cn.coverage.nth)))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
144
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
145 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
146
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
147 logratios.sd.ori = logratios.sd
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
148 if (length(logratios.sd) > 2) {
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
149 logratios.sd = logratios.sd[-length(logratios.sd)]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
150 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
151
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
152 logcov.bins.mean.ori = logcov.bins.mean
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
153 if (length(logcov.bins.mean) > 2){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
154 logcov.bins.mean= logcov.bins.mean[-length(logcov.bins.mean)]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
155 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
156
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
157 fit.sd = lm(log2(logratios.sd) ~ logcov.bins.mean)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
158 fit.sd.a = fit.sd$coefficient[1]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
159 fit.sd.b = fit.sd$coefficient[2]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
160
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
161 fit.sd.fn <- function(x, fit.a, fit.b){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
162 result = 2 ^ (fit.mean.fn(x, fit.a, fit.b))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
163 return (result)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
164 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
165
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
166 # Get the P Values, called the gain/loss
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
167 # with average and sd from each bins
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
168 pVal.list = c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
169 gain.loss = c()
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
170
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
171 for (i in 1:nrow(cn.average.list)){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
172 #print (i)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
173 #logratio = cn.average.list[i]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
174 #logcov = log(normal.rd.ori[i],2)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
175 logratio = adjusted.lr[i]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
176 logcov = logcov.mean[i]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
177 exon.bin = Bin[i]
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
178
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
179 if (length(logratios.sd) > 1){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
180 pVal <- pnorm(logratio, fit.mean.fn(logcov, fit.mean.a, fit.mean.b), fit.sd.fn(logcov, fit.sd.a, fit.sd.b))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
181 } else {
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
182 pVal <- pnorm(logratio, 0, logratios.sd[exon.bin])
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
183 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
184
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
185 if (pVal > 0.5){
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
186 pVal = 1-pVal
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
187 gain.loss = c(gain.loss, "gain")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
188 } else {
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
189 gain.loss = c(gain.loss, "loss")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
190 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
191 pVal.list = c(pVal.list, pVal*2)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
192 }
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
193
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
194 # Get the adjusted P Values
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
195 adjusted.pVal.list = p.adjust(pVal.list, method="BH")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
196
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
197 # Write the output into a tab-delimited text files
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
198 outdf=data.frame(Targeted.Region.ID=ids,Exon.Number=exons,Gene.Sym=gs,Chr, OriStCoordinate, OriEndCoordinate, Mean.of.LogRatio=cn.average.list, Adjusted.Mean.of.LogRatio=adjusted.lr, SD.of.LogRatio=sd, Median.of.LogRatio=median, number.bases, P.Value=pVal.list ,Adjusted.P.Value=adjusted.pVal.list , gain.loss, tumour.rd, normal.rd, tumour.rd.ori, normal.rd.ori, MinLogRatio, MaxLogRatio, BinNumber = Bin)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
199
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
200 #min_normal_rd_for_call=5
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
201 #min_tumour_rd_for_call=0
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
202 #min_avg_cov_for_call=20
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
203 outdf$tumour.rd.ori = outdf$tumour.rd.ori-0.5
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
204 outdf$normal.rd.ori = outdf$normal.rd.ori-0.5
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
205 wh.to.excl = outdf$normal.rd.ori < min_normal_rd_for_call
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
206 wh.to.excl = wh.to.excl | outdf$tumour.rd.ori < min_tumour_rd_for_call
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
207 wh.to.excl = wh.to.excl | (outdf$tumour.rd.ori+outdf$normal.rd.ori)/2 < min_avg_cov_for_call
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
208 outdf$P.Value[wh.to.excl]=NA
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
209 outdf$Adjusted.P.Value[wh.to.excl]=NA
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
210
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
211
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
212 write.table(outdf,out.f,sep="\t",quote=F,row.names=F,col.names=T)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
213
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
214 #Plotting SD
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
215 #a.sd.fn = rep(fit.sd.a, length(logratios.sd.ori))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
216 #b.sd.fn = rep(fit.sd.b, length(logratios.sd.ori))
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
217 #sd.after.fit = fit.sd.fn(logcov.bins.mean.ori, fit.sd.a, fit.sd.b)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
218 #sd.out.f = paste(outf, "/plot/", sample.name, "sd.data_fit.", bins, "bins.txt", sep="")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
219 #sd.outdf = data.frame(SD.Before.Fit = logratios.sd.ori, Log.Coverage = logcov.bins.mean.ori, SD.After.Fit = sd.after.fit, a.for.fitting=a.sd.fn, b.for.fitting=b.sd.fn)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
220 #write.table(sd.outdf, sd.out.f,sep="\t", quote=F, row.names=F, col.names=T)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
221
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
222
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
223 #End of the script
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
224 print ("End of cn_analysis.R")
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
225 print (i)
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
226
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
227
7564f3b1e675 Uploaded
fcaramia
parents:
diff changeset
228