Mercurial > repos > devteam > dwt_cor_avb_all

comparison execute_dwt_cor_aVb_all.R @ 2:e01e8a9a82f4 draft default tip

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"planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_cor_avb_all commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
author devteam
date Mon, 06 Jul 2020 20:31:38 -0400
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1:8564f6927b87 2:e01e8a9a82f4
1 #################################################################################
2 ## code to do all correlation tests of form: motif(a) vs. motif(b)
3 ## add code to create null bands by permuting the original data series
4 ## generate plots and table matrix of correlation coefficients including p-values
5 #################################################################################
6 library("wavethresh");
7 library("waveslim");
8
9 options(echo = FALSE)
10
11 ## normalize data
12 norm <- function(data) {
13 v <- (data - mean(data)) / sd(data);
14 if (sum(is.na(v)) >= 1) {
15 v <- data;
16 }
17 return(v);
18 }
19
20 dwt_cor <- function(data_short, names_short, data_long, names_long, test, pdf, table, filter = 4, bc = "symmetric", method = "kendall", wf = "haar", boundary = "reflection") {
21 print(test);
22 print(pdf);
23 print(table);
24
25 pdf(file = pdf);
26 final_pvalue <- NULL;
27 title <- NULL;
28
29 short_levels <- wavethresh::wd(data_short[, 1], filter.number = filter, bc = bc)$nlevels;
30 title <- c("motif1", "motif2");
31 for (i in 1:short_levels) {
32 title <- c(title, paste(i, "cor", sep = "_"), paste(i, "pval", sep = "_"));
33 }
34 print(title);
35
36 ## normalize the raw data
37 data_short <- apply(data_short, 2, norm);
38 data_long <- apply(data_long, 2, norm);
39
40 ## loop to compare a vs b
41 for (i in seq_len(length(names_short))) {
42 for (j in seq_len(i - 1)) {
43 ## Kendall Tau
44 ## DWT wavelet correlation function
45 ## include significance to compare
46 wave1_dwt <- NULL;
47 wave2_dwt <- NULL;
48 tau_dwt <- NULL;
49 out <- NULL;
50
51 print(names_short[i]);
52 print(names_long[j]);
53
54 ## need exit if not comparing motif(a) vs motif(a)
55 if (names_short[i] == names_long[j]) {
56 stop(paste("motif", names_short[i], "is the same as", names_long[j], sep = " "));
57 }
58 else {
59 wave1_dwt <- waveslim::dwt(data_short[, i], wf = wf, short_levels, boundary = boundary);
60 wave2_dwt <- waveslim::dwt(data_long[, j], wf = wf, short_levels, boundary = boundary);
61 tau_dwt <- vector(length = short_levels)
62
63 ## perform cor test on wavelet coefficients per scale
64 for (level in 1:short_levels) {
65 w1_level <- NULL;
66 w2_level <- NULL;
67 w1_level <- (wave1_dwt[[level]]);
68 w2_level <- (wave2_dwt[[level]]);
69 tau_dwt[level] <- cor.test(w1_level, w2_level, method = method)$estimate;
70 }
71
72 ## CI bands by permutation of time series
73 feature1 <- NULL;
74 feature2 <- NULL;
75 feature1 <- data_short[, i];
76 feature2 <- data_long[, j];
77 null <- NULL;
78 results <- NULL;
79 med <- NULL;
80 cor_25 <- NULL;
81 cor_975 <- NULL;
82
83 for (k in 1:1000) {
84 nk_1 <- NULL;
85 nk_2 <- NULL;
86 null_levels <- NULL;
87 cor <- NULL;
88 null_wave1 <- NULL;
89 null_wave2 <- NULL;
90
91 nk_1 <- sample(feature1, length(feature1), replace = FALSE);
92 nk_2 <- sample(feature2, length(feature2), replace = FALSE);
93 null_levels <- wavethresh::wd(nk_1, filter.number = filter, bc = bc)$nlevels;
94 cor <- vector(length = null_levels);
95 null_wave1 <- waveslim::dwt(nk_1, wf = wf, short_levels, boundary = boundary);
96 null_wave2 <- waveslim::dwt(nk_2, wf = wf, short_levels, boundary = boundary);
97
98 for (level in 1:null_levels) {
99 null_level1 <- NULL;
100 null_level2 <- NULL;
101 null_level1 <- (null_wave1[[level]]);
102 null_level2 <- (null_wave2[[level]]);
103 cor[level] <- cor.test(null_level1, null_level2, method = method)$estimate;
104 }
105 null <- rbind(null, cor);
106 }
107
108 null <- apply(null, 2, sort, na.last = TRUE);
109 cor_25 <- null[25, ];
110 cor_975 <- null[975, ];
111 med <- (apply(null, 2, median, na.rm = TRUE));
112
113 ## plot
114 results <- cbind(tau_dwt, cor_25, cor_975);
115 matplot(results, type = "b", pch = "*", lty = 1, col = c(1, 2, 2), ylim = c(-1, 1), xlab = "Wavelet Scale", ylab = "Wavelet Correlation Kendall's Tau", main = (paste(test, names_short[i], "vs.", names_long[j], sep = " ")), cex.main = 0.75);
116 abline(h = 0);
117
118 ## get pvalues by comparison to null distribution
119 ### modify pval calculation for error type II of T test ####
120 out <- c(names_short[i], names_long[j]);
121 for (m in seq_len(length(tau_dwt))) {
122 print(m);
123 print(tau_dwt[m]);
124 out <- c(out, format(tau_dwt[m], digits = 3));
125 pv <- NULL;
126 if (is.na(tau_dwt[m])) {
127 pv <- "NA";
128 }
129 else{
130 if (tau_dwt[m] >= med[m]) {
131 ## R tail test
132 pv <- (length(which(null[, m] >= tau_dwt[m]))) / (length(na.exclude(null[, m])));
133 }
134 else {
135 if (tau_dwt[m] < med[m]) {
136 ## L tail test
137 pv <- (length(which(null[, m] <= tau_dwt[m]))) / (length(na.exclude(null[, m])));
138 }
139 }
140 }
141 out <- c(out, pv);
142 print(pv);
143 }
144 final_pvalue <- rbind(final_pvalue, out);
145 print(out);
146 }
147 }
148 }
149 colnames(final_pvalue) <- title;
150 write.table(final_pvalue, file = table, sep = "\t", quote = FALSE, row.names = FALSE)
151 dev.off();
152 }
153
154 ## execute
155 ## read in data
156 args <- commandArgs(trailingOnly = TRUE)
157
158 input_data1 <- NULL;
159 input_data2 <- NULL;
160 input_data_short1 <- NULL;
161 input_data_short2 <- NULL;
162 input_data_names_short1 <- NULL;
163 input_data_names_short2 <- NULL;
164
165 input_data1 <- read.delim(args[1]);
166 input_data_short1 <- input_data1[, +c(seq_len(ncol(input_data1)))];
167 input_data_names_short1 <- colnames(input_data_short1);
168
169 input_data2 <- read.delim(args[2]);
170 input_data_short2 <- input_data2[, +c(seq_len(ncol(input_data2)))];
171 input_data_names_short2 <- colnames(input_data_short2);
172
173 # cor test for motif(a) in input_data1 vs motif(b) in input_data2
174 dwt_cor(input_data_short1, input_data_names_short1, input_data_short2, input_data_names_short2, test = "cor_aVb_all", pdf = args[3], table = args[4]);
175 print("done with the correlation test");