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1 <tool id="sartools_edger" name="SARTools edgeR" version="@TOOL_VERSION@+galaxy0">
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3 <description>Compare two or more biological conditions in a RNA-Seq framework with edgeR</description>
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5 <macros>
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6 <import>macros.xml</import>
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7 </macros>
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8
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9 <expand macro="requirements"/>
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10 <expand macro="stdio"/>
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11
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12
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13 <command><![CDATA[
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14
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15 python '$__tool_directory__/abims_sartools_edger_wrapper.py'
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16 ## parameters
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17 @COMMAND_BASIC_PARAMETERS@
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18 @COMMAND_BATCH_PARAM@
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19 --alpha '$advanced_parameters.alpha'
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20 --pAdjustMethod '$advanced_parameters.pAdjustMethod'
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21 --cpmCutoff '$advanced_parameters.cpmCutoff'
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22 --geneSelection '$advanced_parameters.geneSelection'
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23 --normalizationMethod '$advanced_parameters.normalizationMethod'
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24 --colors "'$advanced_parameters.colors'"
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25 --forceCairoGraph '$advanced_parameters.forceCairoGraph'
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26 ## ouputs
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27 @COMMAND_OUTPUTS@
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28
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29 ]]></command>
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30
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31 <inputs>
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32
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33 <expand macro="basic_parameters" />
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34
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35 <section name="advanced_parameters" title="Advanced Parameters" expanded="false" >
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36 <expand macro="batch_param" />
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37 <expand macro="alpha_param" />
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38 <expand macro="padjustmethod_param" />
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39 <param type="integer" value="1" min="0" label="Counts-per-million cut-off to filter low counts" argument="--cpmCutoff" help="Set to 0 to disable filtering. Default is 1." />
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40 <param name="geneSelection" type="select" label="Selection of the features in MDSPlot" argument="--gene.selection" help="Default is 'pairwise'." >
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41 <option value="pairwise" selected="true">pairwise</option>
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42 <option value="common">common</option>
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43 </param>
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44 <param type="select" label="Normalization method in calcNormFactors" argument="--normalizationMethod" help="'TMM' (default), 'RLE' (DESeq method) or 'upperquartile'." >
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45 <option value="TMM" selected="true">TMM</option>
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46 <option value="RLE">RLE</option>
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47 <option value="upperquartile">upperquartile</option>
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48 </param>
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49 <expand macro="colors_param" />
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50 <expand macro="forceCairoGraph_param" />
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51 </section>
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52
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53 </inputs>
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54
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55 <outputs>
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56
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57 <expand macro="outputs" />
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58
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59 </outputs>
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60
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61 <tests>
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62 <test>
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63 <!-- Test with 2 conditions, 2 replicates, 10 features -->
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64 <param name="targetFile" dbkey="?" value="target_small.txt" />
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65 <param name="rawDir" value="raw_small.zip" dbkey="?" ftype="zip"/>
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66 <output name="log">
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67 <assert_contents>
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68 <has_text text="KO vs WT 5 4 9" />
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69 <has_text text="HTML report created" />
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70 </assert_contents>
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71 </output>
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72 </test>
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73 <!-- <test>
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74 --> <!-- NOT WORKING YET: Test with 3 conditions, 3 replicates, 10 features, with batch effect -->
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75 <!-- <param name="targetFile" dbkey="?" value="targetT048_small.txt" />
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76 <param name="rawDir" value="rawT048_small.zip" dbkey="?" ftype="no_unzip.zip"/>
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77 <param name="condRef" value="T0"/>
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78 <param name="condition" value="true"/>
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79 <output name="tables_html" file="SARTools_edgeR_targetT048_small_tables.html" lines_diff="12">
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80 <extra_files type="file" name="T4vsT0.complete.txt" value="SARTools_edgeR_T4vsT0_small.complete.txt"/>
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81 <extra_files type="file" name="T8vsT0.complete.txt" value="SARTools_edgeR_T8vsT0_small.complete.txt"/>
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82 <extra_files type="file" name="T8vsT4.complete.txt" value="SARTools_edgeR_T8vsT4_small.complete.txt"/>
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83 </output>
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84 </test>
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85 --> <test>
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86 <!-- Test with 2 conditions, 2 replicates, 8217 features -->
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87 <param name="targetFile" dbkey="?" value="target.txt" />
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88 <param name="rawDir" value="raw.zip" dbkey="?" ftype="zip"/>
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89 <output name="log">
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90 <assert_contents>
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91 <has_text text="KO vs WT 2691 2713 5404" />
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92 <has_text text="HTML report created" />
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93 </assert_contents>
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94 </output>
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95 </test>
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96 <!-- <test>
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97 --> <!-- NOT WORKING YET: Test with 3 conditions, 3 replicates, 10160 features, with batch effect -->
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98 <!-- <param name="targetFile" dbkey="?" value="targetT048.txt" />
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99 <param name="rawDir" value="rawT048.zip" dbkey="?" ftype="no_unzip.zip"/>
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100 <param name="condRef" value="T0"/>
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101 <param name="condition" value="true"/>
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102 <output name="tables_html" file="SARTools_edgeR_targetT048_tables.html" lines_diff="14">
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103 <extra_files type="file" name="T4vsT0.complete.txt" value="SARTools_edgeR_T4vsT0.complete.txt"/>
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104 <extra_files type="file" name="T8vsT0.complete.txt" value="SARTools_edgeR_T8vsT0.complete.txt"/>
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105 <extra_files type="file" name="T8vsT4.complete.txt" value="SARTools_edgeR_T8vsT4.complete.txt"/>
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106 </output>
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107 </test>
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108 --> </tests>
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109
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110 <help><![CDATA[
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111
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112 @HELP_AUTHORS@
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113
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114 ==============
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115 SARTools edgeR
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116 ==============
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117
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118 -----------
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119 Description
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120 -----------
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121
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122 @HELP_DESCRIPTION@
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123
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124
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125 -----------
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126 Input files
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127 -----------
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128
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129 @HELP_INPUT_FILES@
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130
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131
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132 ----------
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133 Parameters
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134 ----------
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135
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136 @HELP_BASIC_PARAMETERS@
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137 * **batch:** adjustment variable to use as a batch effect, must be a column of the target file (NULL if no batch effect needs to be taken into account);
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138 * **alpha:** significance threshold applied to the adjusted p-values to select the differentially expressed features (default is 0.05);
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139 * **pAdjustMethod:** p-value adjustment method for multiple testing [4, 5] ("BH" by default, "BY" or any value of p.adjust.methods);
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140 * **cpmCutoff:** counts-per-million cut-off to filter low counts (default is 1, set to 0 to disable filtering);
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141 * **gene.selection:** method of selection of the features for the MultiDimensional Scaling plot ("pairwise" by default or common);
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142 * **normalizationMethod:** normalization method in calcNormFactors(): "TMM" (default), "RLE" (DESeq method) or "upperquartile";
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143 * **colors:** colors used for the figures (one per biological condition), 8 are given by default.
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144 * **forceCairoGraph:** TRUE or FALSE (default) to force the use of cairo with options(bitmapType="cairo").
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145
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146
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147 ------------
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148 Output files
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149 ------------
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150
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151 @HELP_OUTPUT_FILES@
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152
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153
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154 ---------------------------------------------------
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155
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156 [1] G.-K. Smyth. Limma: linear models for microarray data. In R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, and W. Huber, editors, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, pages 397–420. Springer, New York, 2005.
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157
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158 [2] S. Anders. HTSeq: Analysing high-throughput sequencing data with Python. http://www-huber.embl.de/users/anders/HTSeq/, 2011.
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159
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160 [3] S. Anders, P.-T. Pyl, and W. Huber. HTSeq - A Python framework to work with high-throughput sequencing data. bioRxiv preprint, 2014. URL: http://dx.doi.org/10.1101/002824.
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161
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162 [4] Y. Benjamini and Y. Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B, 57:289–300, 1995.
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163
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164 [5] Y. Benjamini and D. Yekutieli. The control of the false discovery rate in multiple testing under dependency. Ann. Statist., 29(4):1165–1188, 2001.
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165
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166
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167 ]]></help>
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168
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169 <citations>
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170 <expand macro="common_citations" />
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171 </citations>
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172
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173 </tool>
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