Mercurial > repos > devteam > dwt_ivc_all

comparison execute_dwt_IvC_all.pl @ 0:91fad0f30fd3 draft

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Imported from capsule None
author devteam
date Thu, 23 Jan 2014 12:31:01 -0500
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-1:000000000000 0:91fad0f30fd3
1 #!/usr/bin/perl -w
2 use warnings;
3 use IO::Handle;
4
5 $usage = "execute_dwt_IvC_all.pl [TABULAR.in] [TABULAR.in] [TABULAR.out] [PDF.out] \n";
6 die $usage unless @ARGV == 4;
7
8 #get the input arguments
9 my $firstInputFile = $ARGV[0];
10 my $secondInputFile = $ARGV[1];
11 my $firstOutputFile = $ARGV[2];
12 my $secondOutputFile = $ARGV[3];
13
14 open (INPUT1, "<", $firstInputFile) || die("Could not open file $firstInputFile \n");
15 open (INPUT2, "<", $secondInputFile) || die("Could not open file $secondInputFile \n");
16 open (OUTPUT1, ">", $firstOutputFile) || die("Could not open file $firstOutputFile \n");
17 open (OUTPUT2, ">", $secondOutputFile) || die("Could not open file $secondOutputFile \n");
18 open (ERROR, ">", "error.txt") or die ("Could not open file error.txt \n");
19
20 #save all error messages into the error file $errorFile using the error file handle ERROR
21 STDERR -> fdopen( \*ERROR, "w" ) or die ("Could not direct errors to the error file error.txt \n");
22
23
24 print "There are two input data files: \n";
25 print "The input data file is: $firstInputFile \n";
26 print "The control data file is: $secondInputFile \n";
27
28 # IvC test
29 $test = "IvC";
30
31 # construct an R script to implement the IvC test
32 print "\n";
33
34 $r_script = "get_dwt_IvC_test.r";
35 print "$r_script \n";
36
37 # R script
38 open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
39 print Rcmd "
40 ###########################################################################################
41 # code to do wavelet Indel vs. Control
42 # signal is the difference I-C; function is second moment i.e. variance from zero not mean
43 # to perform wavelet transf. of signal, scale-by-scale analysis of the function
44 # create null bands by permuting the original data series
45 # generate plots and table matrix of correlation coefficients including p-values
46 ############################################################################################
47 library(\"Rwave\");
48 library(\"wavethresh\");
49 library(\"waveslim\");
50
51 options(echo = FALSE)
52
53 # normalize data
54 norm <- function(data){
55 v <- (data - mean(data))/sd(data);
56 if(sum(is.na(v)) >= 1){
57 v <- data;
58 }
59 return(v);
60 }
61
62 dwt_cor <- function(data.short, names.short, data.long, names.long, test, pdf, table, filter = 4, bc = \"symmetric\", wf = \"haar\", boundary = \"reflection\") {
63 print(test);
64 print(pdf);
65 print(table);
66
67 pdf(file = pdf);
68 final_pvalue = NULL;
69 title = NULL;
70
71 short.levels <- wd(data.short[, 1], filter.number = filter, bc = bc)\$nlevels;
72 title <- c(\"motif\");
73 for (i in 1:short.levels){
74 title <- c(title, paste(i, \"moment2\", sep = \"_\"), paste(i, \"pval\", sep = \"_\"), paste(i, \"test\", sep = \"_\"));
75 }
76 print(title);
77
78 # loop to compare a vs a
79 for(i in 1:length(names.short)){
80 wave1.dwt = NULL;
81 m2.dwt = diff = var.dwt = NULL;
82 out = NULL;
83 out <- vector(length = length(title));
84
85 print(names.short[i]);
86 print(names.long[i]);
87
88 # need exit if not comparing motif(a) vs motif(a)
89 if (names.short[i] != names.long[i]){
90 stop(paste(\"motif\", names.short[i], \"is not the same as\", names.long[i], sep = \" \"));
91 }
92 else {
93 # signal is the difference I-C data sets
94 diff<-data.short[,i]-data.long[,i];
95
96 # normalize the signal
97 diff<-norm(diff);
98
99 # function is 2nd moment
100 # 2nd moment m_j = 1/N[sum_N(W_j + V_J)^2] = 1/N sum_N(W_j)^2 + (X_bar)^2
101 wave1.dwt <- dwt(diff, wf = wf, short.levels, boundary = boundary);
102 var.dwt <- wave.variance(wave1.dwt);
103 m2.dwt <- vector(length = short.levels)
104 for(level in 1:short.levels){
105 m2.dwt[level] <- var.dwt[level, 1] + (mean(diff)^2);
106 }
107
108 # CI bands by permutation of time series
109 feature1 = feature2 = NULL;
110 feature1 = data.short[, i];
111 feature2 = data.long[, i];
112 null = results = med = NULL;
113 m2_25 = m2_975 = NULL;
114
115 for (k in 1:1000) {
116 nk_1 = nk_2 = NULL;
117 m2_null = var_null = NULL;
118 null.levels = null_wave1 = null_diff = NULL;
119 nk_1 <- sample(feature1, length(feature1), replace = FALSE);
120 nk_2 <- sample(feature2, length(feature2), replace = FALSE);
121 null.levels <- wd(nk_1, filter.number = filter, bc = bc)\$nlevels;
122 null_diff <- nk_1-nk_2;
123 null_diff <- norm(null_diff);
124 null_wave1 <- dwt(null_diff, wf = wf, short.levels, boundary = boundary);
125 var_null <- wave.variance(null_wave1);
126 m2_null <- vector(length = null.levels);
127 for(level in 1:null.levels){
128 m2_null[level] <- var_null[level, 1] + (mean(null_diff)^2);
129 }
130 null= rbind(null, m2_null);
131 }
132
133 null <- apply(null, 2, sort, na.last = TRUE);
134 m2_25 <- null[25,];
135 m2_975 <- null[975,];
136 med <- apply(null, 2, median, na.rm = TRUE);
137
138 # plot
139 results <- cbind(m2.dwt, m2_25, m2_975);
140 matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2), xlab = \"Wavelet Scale\", ylab = c(\"Wavelet 2nd Moment\", test), main = (names.short[i]), cex.main = 0.75);
141 abline(h = 1);
142
143 # get pvalues by comparison to null distribution
144 out <- c(names.short[i]);
145 for (m in 1:length(m2.dwt)){
146 print(paste(\"scale\", m, sep = \" \"));
147 print(paste(\"m2\", m2.dwt[m], sep = \" \"));
148 print(paste(\"median\", med[m], sep = \" \"));
149 out <- c(out, format(m2.dwt[m], digits = 4));
150 pv = NULL;
151 if(is.na(m2.dwt[m])){
152 pv <- \"NA\";
153 }
154 else {
155 if (m2.dwt[m] >= med[m]){
156 # R tail test
157 tail <- \"R\";
158 pv <- (length(which(null[, m] >= m2.dwt[m])))/(length(na.exclude(null[, m])));
159 }
160 else{
161 if (m2.dwt[m] < med[m]){
162 # L tail test
163 tail <- \"L\";
164 pv <- (length(which(null[, m] <= m2.dwt[m])))/(length(na.exclude(null[, m])));
165 }
166 }
167 }
168 out <- c(out, pv);
169 print(pv);
170 out <- c(out, tail);
171 }
172 final_pvalue <-rbind(final_pvalue, out);
173 print(out);
174 }
175 }
176
177 colnames(final_pvalue) <- title;
178 write.table(final_pvalue, file = table, sep = \"\\t\", quote = FALSE, row.names = FALSE);
179 dev.off();
180 }\n";
181
182 print Rcmd "
183 # execute
184 # read in data
185
186 inputData <- read.delim(\"$firstInputFile\");
187 inputDataNames <- colnames(inputData);
188
189 controlData <- read.delim(\"$secondInputFile\");
190 controlDataNames <- colnames(controlData);
191
192 # call the test function to implement IvC test
193 dwt_cor(inputData, inputDataNames, controlData, controlDataNames, test = \"$test\", pdf = \"$secondOutputFile\", table = \"$firstOutputFile\");
194 print (\"done with the correlation test\");
195 \n";
196
197 print Rcmd "#eof\n";
198
199 close Rcmd;
200
201 system("echo \"wavelet IvC test started on \`hostname\` at \`date\`\"\n");
202 system("R --no-restore --no-save --no-readline < $r_script > $r_script.out\n");
203 system("echo \"wavelet IvC test ended on \`hostname\` at \`date\`\"\n");
204
205 #close the input and output and error files
206 close(ERROR);
207 close(OUTPUT2);
208 close(OUTPUT1);
209 close(INPUT2);
210 close(INPUT1);