Mercurial > repos > iuc > ggplot2_heatmap

annotate ggplot2_heatmap.xml @ 6:3f13d3158bf5 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit 843a94f53c808d098def353b0bc5f7f554d9e1af
author iuc
date Fri, 09 Dec 2022 22:39:41 +0000
parents f6f9f2ec14bc
children 48fc850095ba
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f6f9f2ec14bc "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit 4b44f8f834de15fd34e2fdc5e4aed282069f73af"
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1 <tool id="ggplot2_heatmap" name="Heatmap w ggplot" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.01">
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5acfed72fb36 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit e0d4688a59e6eeba33adcfe803ac43d0bc2863e7"
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2 <expand macro="bio_tools"/>
0
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3 <macros>
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4 <import>macros.xml</import>
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5 </macros>
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6 <requirements>
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f6f9f2ec14bc "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit 4b44f8f834de15fd34e2fdc5e4aed282069f73af"
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7 <requirement type="package" version="1.1.1">r-cowplot</requirement>
f6f9f2ec14bc "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit 4b44f8f834de15fd34e2fdc5e4aed282069f73af"
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8 <requirement type="package" version="0.4.5">r-egg</requirement>
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9 <requirement type="package" version="0.1.23">r-ggdendro</requirement>
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10 <requirement type="package" version="1.0.10">r-dplyr</requirement>
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f6f9f2ec14bc "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit 4b44f8f834de15fd34e2fdc5e4aed282069f73af"
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11 <requirement type="package" version="1.4.4">r-reshape2</requirement>
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12 <requirement type="package" version="2.1.0">r-svglite</requirement>
0
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13 </requirements>
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14 <command detect_errors="exit_code"><![CDATA[
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15 cat '$script' &&
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16 Rscript '$script'
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17 ]]></command>
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18 <configfiles>
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19 <configfile name="script"><![CDATA[
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20 @R_INIT@
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21
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22 ## Import library
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23
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24 library(ggplot2)
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25 library(cowplot)
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26 library(egg)
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27 library(dplyr)
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28 library(ggdendro)
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29 library(reshape2)
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30
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31 input <- '$input1'
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32 header <- ${inputdata.header}
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33 rowname_index <- as.integer('$inputdata.row_names_index')
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34
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35 transform <- '$adv.transform'
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36
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37 ## read table with or with out header or row_names
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38 if(rowname_index > 0){
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39 df <- read.table(input, header = header, row.names = rowname_index, sep = "\t")
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40 }else{
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41 df <- read.table(input, header = header, sep = "\t")
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42 }
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43
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44 hclust_fun = function(x) hclust(x, method="complete")
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45 dist_fun = function(x) dist(x, method="maximum")
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46 distfun=dist_fun
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47 hclustfun=hclust_fun
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48
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49 plot_mat <- df
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50
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51 ## transform dataset
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52 if(transform == "log2"){
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53 plot_mat <- log2(plot_mat)
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54 cat("\n ", transform, " transformed")
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55 }else if(transform == "log2plus1"){
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56 plot_mat <- log2(plot_mat+1)
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57 cat("\n ", transform, " transformed")
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58 }else if(transform == "log10"){
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59 plot_mat <- log10(plot_mat)
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60 cat("\n ", transform, " transformed")
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61 }else if(transform == "log10plus1"){
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62 plot_mat <- log10(plot_mat+1)
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63 cat("\n ", transform, " transformed")
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64 }else{
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65 plot_mat <- plot_mat
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66 }
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67
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68 #if $adv.colorscheme == "whrd"
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69 colorscale = scale_fill_gradient(low="white", high="red", guide="colorbar")
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70 #elif $adv.colorscheme == "whblu"
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71 colorscale = scale_fill_gradient(low="white", high="blue", guide="colorbar")
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72 #elif $adv.colorscheme == "blwhre"
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73 colorscale = scale_fill_gradient2(low="blue", mid="white", high="red", guide="colorbar")
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74 #end if
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75
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76 plot_mat["rows"] <- row.names(plot_mat)
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77 plot_mat.melt <- melt(plot_mat, id.vars = "rows")
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78 names(plot_mat.melt)[2] <- "cols"
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79
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80 #if $adv.cluster:
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82 plot_mat.dendo <- as.dendrogram(hclust(d = dist(x = subset(plot_mat, select = -rows))))
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83
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84 plot_mat.dendo.order <- order.dendrogram(plot_mat.dendo)
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85
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86 gg_rows = ggdendrogram(data = plot_mat.dendo, rotate = FALSE) +
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87 theme(axis.text.y = element_text(size = 6), axis.text.x = element_blank())
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88
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89 plot_mat.melt[,"rows"] <- factor(x = plot_mat.melt[,"rows"],
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90 levels = unique(plot_mat.melt[,"rows"])[plot_mat.dendo.order],
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91 ordered = TRUE)
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92
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93 plot_mat.dendo <- as.dendrogram(hclust(d = dist(x = t(subset(plot_mat, select = -rows)))))
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94 plot_mat.dendo.order <- order.dendrogram(plot_mat.dendo)
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95
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96 gg_cols = ggdendrogram(data = plot_mat.dendo, rotate = TRUE) +
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97 theme(axis.text.x = element_text(size = 6), axis.text.y = element_blank())
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98
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99 plot_mat.melt[,"cols"] <- factor(x = plot_mat.melt[,"cols"],
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100 levels = unique(plot_mat.melt[,"cols"])[plot_mat.dendo.order],
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101 ordered = TRUE)
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102
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103 ## plot the heatmap
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104 gg_hm = plot_mat.melt %>%
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105 ggplot(aes(x = rows, y = cols, fill = value)) +
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106 geom_tile() +
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107 theme(legend.position = "bottom", axis.title.x = element_blank(), axis.title.y = element_blank(),
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108 axis.text.x = element_text(angle = 90, hjust = 1)) +
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109 colorscale
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110
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111 gg_empty = plot_mat.melt %>%
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112 ggplot(aes(x = cols, y = value)) +
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113 geom_blank() +
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114 theme(axis.text = element_blank(),
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115 axis.title = element_blank(),
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116 line = element_blank(),
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117 panel.background = element_blank())
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118
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119 plot_out <- ggarrange(
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120 gg_rows, gg_empty, gg_hm, gg_cols,
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121 nrow = 2, ncol = 2, widths = c(3, 1), heights = c(1, 3), newpage =F)
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122
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123 #else
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124
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125 ## plot the heatmap
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126 gg_hm = plot_mat.melt %>%
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127 ggplot(aes(x = rows, y = cols, fill = value)) +
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128 geom_tile() + ggtitle('$title') +
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129 theme(legend.position = "bottom", axis.title.x = element_blank(), axis.title.y = element_blank(), axis.text.x = element_text(angle = 90, hjust = 1)) +
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130 colorscale
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131
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132 plot_out <- gg_hm
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133
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134 #end if
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135
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136 @SAVE_OUTPUT@
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137 ]]></configfile>
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138 </configfiles>
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139 <inputs>
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140 <expand macro="read_complex_input"/>
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141 <expand macro="title"/>
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142 <!-- Advanced Options -->
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143 <section name="adv" title="Advanced Options" expanded="false">
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144 <expand macro="transform" />
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145 <param name="cluster" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Enable data clustering" />
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146 <param name="colorscheme" type="select" label="Heatmap colorscheme" >
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147 <option value="whrd" selected="true">White to red</option>
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148 <option value="whblu">White to blue</option>
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149 <option value="blwhre">Blue to white to red</option>
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150 </param>
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151 </section>
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152 <!-- Output Options -->
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153 <section name="out" title="Output Options" expanded="true">
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154 <expand macro="dimensions" />
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155 </section>
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156 </inputs>
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157 <outputs>
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158 <expand macro="additional_output" />
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159 </outputs>
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160 <tests>
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161 <test>
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162 <param name="input1" value="mtcars.txt" ftype="tabular"/>
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163 <conditional name="inputdata">
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164 <param name="input_type" value="with_header_rownames"/>
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165 <param name="header" value="TRUE"/>
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166 <param name="row_names_index" value="1"/>
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167 <param name="sample_name_orientation" value="TRUE"/>
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168 </conditional>
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169 <param name="transform" value="log10plus1"/>
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170 <param name="cluster" value="true"/>
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171 <param name="colorscheme" value="blwhre"/>
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172 <param name="additional_output_format" value="pdf"/>
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173 <output name="output2" file="ggplot_heatmap_result1.pdf" compare="sim_size"/>
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174 </test>
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175 </tests>
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176 <help><![CDATA[
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177 This tool will generate a clustered heatmap of your data. More customization options will be added, for now the heatmap uses a red coloring scheme and clustering is performed using the "maximum" similarity measure and the "complete" hierarchical clustering measure.
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178
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179 Input data should have row labels in the first column and column labels. For example, the row labels (the first column) should represent gene IDs and the column labels should represent sample IDs.
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180 ]]></help>
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181 <citations>
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182 </citations>
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183 </tool>