Mercurial > repos > iuc > ggplot2_heatmap

annotate ggplot2_heatmap.xml @ 0:d9b2b499a9dd draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit f9fb73a88ab8b52ce11c25a966d4fe99e67c9fbf
author iuc
date Mon, 11 Jun 2018 16:02:55 -0400
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children 5acfed72fb36
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d9b2b499a9dd planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit f9fb73a88ab8b52ce11c25a966d4fe99e67c9fbf
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1 <tool id="ggplot2_heatmap" name="Heatmap w ggplot" version="@VERSION@">
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2 <macros>
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3 <import>macros.xml</import>
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4 </macros>
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5 <requirements>
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6 <requirement type="package" version="0.9.2">r-cowplot</requirement>
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7 <requirement type="package" version="0.2.0">r-egg</requirement>
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8 <requirement type="package" version="0.1_20">r-ggdendro</requirement>
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9 <requirement type="package" version="0.7.4">r-dplyr</requirement>
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10 <requirement type="package" version="1.4.3">r-reshape2</requirement>
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11 <requirement type="package" version="1.2.1">r-svglite</requirement>
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12 </requirements>
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13 <command detect_errors="exit_code"><![CDATA[
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14 cat '$script' &&
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15 Rscript '$script'
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16 ]]></command>
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17 <configfiles>
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18 <configfile name="script"><![CDATA[
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19 @R_INIT@
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20
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21 ## Import library
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22
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23 library(ggplot2)
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24 library(cowplot)
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25 library(egg)
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26 library(dplyr)
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27 library(ggdendro)
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28 library(reshape2)
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29
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30 input <- '$input1'
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31 header <- ${inputdata.header}
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32 rowname_index <- as.integer('$inputdata.row_names_index')
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33
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34 transform <- '$adv.transform'
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35
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36 ## read table with or with out header or row_names
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37 if(rowname_index > 0){
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38 df <- read.table(input, header = header, row.names = rowname_index, sep = "\t")
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39 }else{
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40 df <- read.table(input, header = header, sep = "\t")
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41 }
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42
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43 hclust_fun = function(x) hclust(x, method="complete")
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44 dist_fun = function(x) dist(x, method="maximum")
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45 distfun=dist_fun
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46 hclustfun=hclust_fun
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47
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48 plot_mat <- df
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49
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50 ## transform dataset
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51 if(transform == "log2"){
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52 plot_mat <- log2(plot_mat)
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53 cat("\n ", transform, " transformed")
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54 }else if(transform == "log2plus1"){
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55 plot_mat <- log2(plot_mat+1)
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56 cat("\n ", transform, " transformed")
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57 }else if(transform == "log10"){
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58 plot_mat <- log10(plot_mat)
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59 cat("\n ", transform, " transformed")
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60 }else if(transform == "log10plus1"){
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61 plot_mat <- log10(plot_mat+1)
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62 cat("\n ", transform, " transformed")
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63 }else{
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64 plot_mat <- plot_mat
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65 }
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66
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67 #if $adv.colorscheme == "whrd"
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68 colorscale = scale_fill_gradient(low="white", high="red", guide="colorbar")
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69 #elif $adv.colorscheme == "whblu"
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70 colorscale = scale_fill_gradient(low="white", high="blue", guide="colorbar")
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71 #elif $adv.colorscheme == "blwhre"
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72 colorscale = scale_fill_gradient2(low="blue", mid="white", high="red", guide="colorbar")
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73 #end if
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74
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75 plot_mat["rows"] <- row.names(plot_mat)
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76 plot_mat.melt <- melt(plot_mat, id.vars = "rows")
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77 names(plot_mat.melt)[2] <- "cols"
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78
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79 #if $adv.cluster:
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80
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81 plot_mat.dendo <- as.dendrogram(hclust(d = dist(x = subset(plot_mat, select = -rows))))
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82
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83 plot_mat.dendo.order <- order.dendrogram(plot_mat.dendo)
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84
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85 gg_rows = ggdendrogram(data = plot_mat.dendo, rotate = FALSE) +
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86 theme(axis.text.y = element_text(size = 6), axis.text.x = element_blank())
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87
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88 plot_mat.melt[,"rows"] <- factor(x = plot_mat.melt[,"rows"],
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89 levels = unique(plot_mat.melt[,"rows"])[plot_mat.dendo.order],
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90 ordered = TRUE)
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91
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92 plot_mat.dendo <- as.dendrogram(hclust(d = dist(x = t(subset(plot_mat, select = -rows)))))
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93 plot_mat.dendo.order <- order.dendrogram(plot_mat.dendo)
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94
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95 gg_cols = ggdendrogram(data = plot_mat.dendo, rotate = TRUE) +
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96 theme(axis.text.x = element_text(size = 6), axis.text.y = element_blank())
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97
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98 plot_mat.melt[,"cols"] <- factor(x = plot_mat.melt[,"cols"],
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99 levels = unique(plot_mat.melt[,"cols"])[plot_mat.dendo.order],
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100 ordered = TRUE)
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101
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102 ## plot the heatmap
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103 gg_hm = plot_mat.melt %>%
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104 ggplot(aes(x = rows, y = cols, fill = value)) +
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105 geom_tile() +
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106 theme(legend.position = "bottom", axis.title.x = element_blank(), axis.title.y = element_blank(),
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107 axis.text.x = element_text(angle = 90, hjust = 1)) +
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108 colorscale
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109
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110 gg_empty = plot_mat.melt %>%
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111 ggplot(aes(x = cols, y = value)) +
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112 geom_blank() +
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113 theme(axis.text = element_blank(),
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114 axis.title = element_blank(),
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115 line = element_blank(),
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116 panel.background = element_blank())
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117
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118 plot_out <- ggarrange(
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119 gg_rows, gg_empty, gg_hm, gg_cols,
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120 nrow = 2, ncol = 2, widths = c(3, 1), heights = c(1, 3), newpage =F)
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121
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122 #else
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123
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124 ## plot the heatmap
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125 gg_hm = plot_mat.melt %>%
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126 ggplot(aes(x = rows, y = cols, fill = value)) +
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127 geom_tile() + ggtitle('$title') +
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128 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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129 colorscale
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130
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131 plot_out <- gg_hm
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132
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133 #end if
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134
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135 @SAVE_OUTPUT@
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136 ]]></configfile>
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137 </configfiles>
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138 <inputs>
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139 <expand macro="read_complex_input"/>
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140 <expand macro="title"/>
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141 <!-- Advanced Options -->
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142 <section name="adv" title="Advanced Options" expanded="false">
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143 <expand macro="transform" />
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144 <param name="cluster" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Enable data clustering" />
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145 <param name="colorscheme" type="select" label="Heatmap colorscheme" >
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146 <option value="whrd" selected="true">White to red</option>
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147 <option value="whblu">White to blue</option>
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148 <option value="blwhre">Blue to white to red</option>
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149 </param>
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150 </section>
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151 <!-- Output Options -->
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152 <section name="out" title="Output Options" expanded="true">
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153 <expand macro="dimensions" />
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154 </section>
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155 </inputs>
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156 <outputs>
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157 <expand macro="additional_output" />
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158 </outputs>
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159 <tests>
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160 <test>
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161 <param name="input1" value="mtcars.txt" ftype="tabular"/>
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162 <conditional name="inputdata">
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163 <param name="input_type" value="with_header_rownames"/>
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164 <param name="header" value="TRUE"/>
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165 <param name="row_names_index" value="1"/>
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166 <param name="sample_name_orientation" value="TRUE"/>
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167 </conditional>
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168 <param name="transform" value="log10plus1"/>
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169 <param name="cluster" value="true"/>
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170 <param name="colorscheme" value="blwhre"/>
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171 <param name="additional_output_format" value="pdf"/>
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172 <output name="output2" file="ggplot_heatmap_result1.pdf" compare="sim_size"/>
d9b2b499a9dd planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit f9fb73a88ab8b52ce11c25a966d4fe99e67c9fbf
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173 </test>
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174 </tests>
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175 <help><![CDATA[
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176 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.
d9b2b499a9dd planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit f9fb73a88ab8b52ce11c25a966d4fe99e67c9fbf
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177
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178 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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179 ]]></help>
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180 <citations>
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181 </citations>
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182 </tool>