Mercurial > repos > devteam > dwt_var_perclass

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"planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
author devteam
date Mon, 06 Jul 2020 18:12:51 +0000
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0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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1 ######################################################################
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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2 ## plot power spectra, i.e. wavelet variance by class
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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3 ## add code to create null bands by permuting the original data series
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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4 ## get class of maximum significant variance per feature
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5 ## generate plots and table matrix of variance including p-values
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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6 ######################################################################
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7 library("wavethresh");
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8 library("waveslim");
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10 options(echo = FALSE)
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0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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12 ## normalize data
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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13 norm <- function(data) {
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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14 v <- (data - mean(data)) / sd(data);
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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15 if (sum(is.na(v)) >= 1) {
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16 v <- data;
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17 }
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18 return(v);
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19 }
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21 dwt_var_permut_get_max <- function(data, names, outfile, filter = 4, bc = "symmetric", method = "kendall", wf = "haar", boundary = "reflection") {
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22 max_var <- NULL;
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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23 matrix <- NULL;
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24 title <- NULL;
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25 final_pvalue <- NULL;
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26 short_levels <- NULL;
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27 scale <- NULL;
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29 print(names);
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31 par(mfcol = c(length(names), length(names)), mar = c(0, 0, 0, 0), oma = c(4, 3, 3, 2), xaxt = "s", cex = 1, las = 1);
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33 short_levels <- wavethresh::wd(data[, 1], filter.number = filter, bc = bc)$nlevels;
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35 title <- c("motif");
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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36 for (i in seq_len(short_levels)) {
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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37 title <- c(title, paste(i, "var", sep = "_"), paste(i, "pval", sep = "_"), paste(i, "test", sep = "_"));
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38 }
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39 print(title);
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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40
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41 ## normalize the raw data
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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42 data <- apply(data, 2, norm);
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43
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44 for (i in seq_len(length(names))) {
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45 for (j in seq_len(length(names))) {
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46 temp <- NULL;
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47 results <- NULL;
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48 wave1_dwt <- NULL;
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49 out <- NULL;
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50
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51 out <- vector(length = length(title));
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52 temp <- vector(length = short_levels);
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53
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54 if (i != j) {
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55 plot(temp, type = "n", axes = FALSE, xlab = NA, ylab = NA);
0c1388b563a8 "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_var_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
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56 box(col = "grey");
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57 grid(ny = 0, nx = NULL);
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58 } else {
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59
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60 wave1_dwt <- waveslim::dwt(data[, i], wf = wf, short_levels, boundary = boundary);
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61
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62 temp_row <- (short_levels + 1) * -1;
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63 temp_col <- 1;
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64 temp <- waveslim::wave.variance(wave1_dwt)[temp_row, temp_col];
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65
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66 ##permutations code :
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67 feature1 <- NULL;
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68 null <- NULL;
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69 var_25 <- NULL;
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70 var_975 <- NULL;
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71 med <- NULL;
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72
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73 feature1 <- data[, i];
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74 for (k in seq_len(1000)) {
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75 nk_1 <- NULL;
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76 null_levels <- NULL;
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77 var <- NULL;
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78 null_wave1 <- NULL;
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79
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80 nk_1 <- sample(feature1, length(feature1), replace = FALSE);
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81 null_levels <- wavethresh::wd(nk_1, filter.number = filter, bc = bc)$nlevels;
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82 var <- vector(length = length(null_levels));
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83 null_wave1 <- waveslim::dwt(nk_1, wf = wf, short_levels, boundary = boundary);
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84 var <- waveslim::wave.variance(null_wave1)[-8, 1];
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85 null <- rbind(null, var);
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86 }
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87 null <- apply(null, 2, sort, na.last = TRUE);
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88 var_25 <- null[25, ];
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89 var_975 <- null[975, ];
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90 med <- (apply(null, 2, median, na.rm = TRUE));
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91
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92 ## plot
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93 results <- cbind(temp, var_25, var_975);
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94 matplot(results, type = "b", pch = "*", lty = 1, col = c(1, 2, 2), axes = F);
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95
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96 ## get pvalues by comparison to null distribution
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97 out <- (names[i]);
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98 for (m in seq_len(length(temp))) {
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99 print(paste("scale", m, sep = " "));
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100 print(paste("var", temp[m], sep = " "));
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101 print(paste("med", med[m], sep = " "));
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102 pv <- NULL;
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103 tail <- NULL;
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104 out <- c(out, format(temp[m], digits = 3));
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105 if (temp[m] >= med[m]) {
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106 ## R tail test
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107 print("R");
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108 tail <- "R";
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109 pv <- (length(which(null[, m] >= temp[m]))) / (length(na.exclude(null[, m])));
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110
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111 } else {
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112 ## L tail test
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113 print("L");
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114 tail <- "L";
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115 pv <- (length(which(null[, m] <= temp[m]))) / (length(na.exclude(null[, m])));
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116 }
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117 out <- c(out, pv);
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118 print(pv);
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119 out <- c(out, tail);
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120 ## get variances outside null bands by comparing temp to null
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121 ### temp stores variance for each scale, and null stores permuted variances for null bands
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122 if (temp[m] <= var_975[m]) {
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123 temp[m] <- NA;
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124 }
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125 }
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126 final_pvalue <- rbind(final_pvalue, out);
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127 matrix <- rbind(matrix, temp)
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128 }
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129 ## labels
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130 if (i == 1) {
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131 mtext(names[j], side = 2, line = 0.5, las = 3, cex = 0.25);
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132 }
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133 if (j == 1) {
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134 mtext(names[i], side = 3, line = 0.5, cex = 0.25);
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135 }
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136 if (j == length(names)) {
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137 axis(1, at = (1:short_levels), las = 3, cex.axis = 0.5);
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138 }
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139 }
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140 }
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141 colnames(final_pvalue) <- title;
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142
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143 ## get maximum variance larger than expectation by comparison to null bands
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144 varnames <- vector();
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145 for (i in seq_len(length(names))) {
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146 name1 <- paste(names[i], "var", sep = "_")
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147 varnames <- c(varnames, name1)
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148 }
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149 rownames(matrix) <- varnames;
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150 colnames(matrix) <- (1:short_levels);
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151 max_var <- names;
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152 scale <- vector(length = length(names));
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153 for (x in seq_len(nrow(matrix))) {
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154 if (length(which.max(matrix[x, ])) == 0) {
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155 scale[x] <- NA;
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156 } else{
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157 scale[x] <- colnames(matrix)[which.max(matrix[x, ])];
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158 }
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159 }
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160 max_var <- cbind(max_var, scale);
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161 write.table(max_var, file = outfile, sep = "\t", quote = FALSE, row.names = FALSE, append = TRUE);
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162 return(final_pvalue);
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163 }
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164
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165 ## execute
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166 ## read in data
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167 args <- commandArgs(trailingOnly = TRUE)
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168
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169 data_test <- NULL;
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170 data_test <- read.delim(args[1]);
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171
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172 count <- ncol(data_test)
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173 print(paste("The number of columns in the input file is: ", count));
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174
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175 # check if the number of motifs is not a multiple of 12, and round up is so
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176 if (count %% 12 != 0) {
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177 print("the number of motifs is not a multiple of 12")
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178 count2 <- ceiling(count / 12);
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179 }else{
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180 print("the number of motifs is a multiple of 12")
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181 count2 <- count / 12
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182 }
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183 print(paste("There will be", count2, "subfiles"))
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184
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185 pdf(file = args[4], width = 11, height = 8);
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186
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187 ## loop to read and execute on all count2 subfiles
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188 final <- NULL;
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189 for (x in seq_len(count2)) {
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190 sub <- NULL;
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191 sub_names <- NULL;
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192 a <- NULL;
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193 b <- NULL;
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194
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195 a <- ((x - 1) * 12 + 1);
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196 b <- x * 12;
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197
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198 if (x < count2) {
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199 sub <- data_test[, +c(a:b)];
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200 sub_names <- colnames(data_test)[a:b];
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201 final <- rbind(final, dwt_var_permut_get_max(sub, sub_names, args[2]));
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202 }
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203 else{
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204 sub <- data_test[, +c(a:ncol(data_test))];
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205 sub_names <- colnames(data_test)[a:ncol(data_test)];
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206 final <- rbind(final, dwt_var_permut_get_max(sub, sub_names, args[2]));
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207 }
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208 }
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209
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210 dev.off();
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211
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212 write.table(final, file = args[3], sep = "\t", quote = FALSE, row.names = FALSE);