annotate edger-repenrich.xml @ 14:bf866bedd4b4 draft

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/repenrich commit 205141a3f695f202d5c3e01e6ab3b2b869fe62b5
author artbio
date Sat, 20 Apr 2024 12:13:52 +0000
parents 530626b0757c
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1 <tool id="edger-repenrich" name="edgeR-repenrich" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
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2 <description>Determines differentially expressed features from RepEnrich counts</description>
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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 <expand macro="edgeR_requirements"/>
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7 <stdio>
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8 <regex match="Execution halted"
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9 source="both"
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10 level="fatal"
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11 description="Execution halted." />
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12 <regex match="Error in"
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13 source="both"
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14 level="fatal"
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15 description="An undefined error occurred, please check your input carefully and contact your administrator." />
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16 <regex match="Fatal error"
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17 source="both"
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18 level="fatal"
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19 description="An undefined error occurred, please check your input carefully and contact your administrator." />
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20 </stdio>
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21 <version_command>
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22 <![CDATA[
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23 echo $(R --version | grep version | grep -v GNU)", edgeR version" $(R --vanilla --slave -e "library(edgeR) &&
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24 cat(sessionInfo()\$otherPkgs\$edgeR\$Version)" 2> /dev/null | grep -v -i "WARNING: ")
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25 ]]>
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26 </version_command>
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27 <command>
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28 <![CDATA[
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29 #import json
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30 Rscript '${__tool_directory__}/edgeR_repenrich.R'
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31 --factorName '$factorName'
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32
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33 --levelNameA '$factorLevel_A'
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34 #set $factorlevelsA = list()
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35 #for $file in $countsFiles_A:
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36 $factorlevelsA.append(str($file))
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37 #end for
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38 $factorlevelsA.reverse()
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39 --levelAfiles '#echo json.dumps(factorlevelsA)#'
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40
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41 --levelNameB '$factorLevel_B'
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42 #set $factorlevelsB = list()
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43 #for $file in $countsFiles_B:
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44 $factorlevelsB.append(str($file))
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45 #end for
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46 $factorlevelsB.reverse()
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47 --levelBfiles '#echo json.dumps(factorlevelsB)#'
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48
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49 -o 'edger_out'
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50
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51 -p '$plots'
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52 #if $normCounts:
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53 -n '$counts_out'
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54 #end if
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55 -o '$edger_out'
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56 ]]>
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57 </command>
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58 <inputs>
3
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59 <param name="factorName" type="text" value="FactorName" label="Specify a factor name, e.g. genotype or age or drug_x"
0
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60 help="Only letters, numbers and underscores will be retained in this field">
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61 <sanitizer>
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62 <valid initial="string.letters,string.digits"><add value="_" /></valid>
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63 </sanitizer>
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64 </param>
3
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65 <param name="factorLevel_A" type="text" value="FactorLevel1" label="Specify a factor level, typical values could be 'mutant' or 'Drug_X'"
0
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66 help="Only letters, numbers and underscores will be retained in this field">
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67 <sanitizer>
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68 <valid initial="string.letters,string.digits"><add value="_" /></valid>
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69 </sanitizer>
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70 </param>
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71 <param name="countsFiles_A" type="data" format="tabular" multiple="true" label="Counts file(s)" help="Count files must have been generated by repenrich" />
3
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72 <param name="factorLevel_B" type="text" value="FactorLevel2" label="Specify a factor level, typical values could be 'wildtype' or 'control'"
0
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73 help="Only letters, numbers and underscores will be retained in this field">
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74 <sanitizer>
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75 <valid initial="string.letters,string.digits"><add value="_" /></valid>
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76 </sanitizer>
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77 </param>
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78 <param name="countsFiles_B" type="data" format="tabular" multiple="true" label="Counts file(s)" help="Count files must have been generated by repenrich tool" />
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79 <param name="normCounts" type="boolean" truevalue="1" falsevalue="0" checked="false"
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80 label="Output normalized counts table" />
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81 </inputs>
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82 <outputs>
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83 <data format="tabular" name="edger_out" label="edgeR: ${factorLevel_A} compared to ${factorLevel_B}">
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84 <actions>
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85 <action name="column_names" type="metadata" default="Tag,log2(FC),FDR,Class,Type" />
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86 </actions>
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87 </data>
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88 <data format="pdf" name="plots" label="edgeR plots" />
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89 <data format="tabular" name="counts_out" label="Normalized counts file">
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90 <filter>normCounts == True</filter>
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91 </data>
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92 </outputs>
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93 <tests>
11
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94 <test expect_num_outputs="3">
0
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95 <param name="factorName" value="Genotype"/>
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96 <param name="factorLevel_A" value="Mutant"/>
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97 <param name="countsFiles_A" value="355_fraction_counts.tab,356_fraction_counts.tab"/>
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98 <param name="factorLevel_B" value="Wildtype"/>
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99 <param name="countsFiles_B" value="353_fraction_counts.tab,354_fraction_counts.tab"/>
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100 <param name="normCounts" value="True"/>
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101 <output name="counts_out" file="Normalized_counts_file.tab"/>
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102 <output name="plots" file="edgeR_plots.pdf"/>
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103 <output name="edger_out" file="edgeR_result_file.tab"/>
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104
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105 </test>
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106 </tests>
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107 <help>
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108 <![CDATA[
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109 .. class:: infomark
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110
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111 **What it does**
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112
1
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113 Estimate Distance between samples (MDS) and Biological Coefficient Variation (BCV) in count
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114 data from high-throughput sequencing assays and test for differential expression using edgeR_.
0
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115
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116 **Inputs**
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117
1
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118 edger-repenrich takes count tables generated by repenrich as inputs. A repenrich count table looks
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119 like:
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120
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121 ============== ========== ========== ==========
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122 LSU-rRNA_Dme rRNA rRNA 3659329
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123 -------------- ---------- ---------- ----------
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124 FW3_DM LINE Jockey 831
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125 -------------- ---------- ---------- ----------
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126 DMTOM1_LTR LTR Gypsy 1004
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127 -------------- ---------- ---------- ----------
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128 R1_DM LINE R1 7343
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129 -------------- ---------- ---------- ----------
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130 TAHRE LINE Jockey 4560
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131 -------------- ---------- ---------- ----------
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132 G4_DM LINE Jockey 3668
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133 -------------- ---------- ---------- ----------
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134 BS LINE Jockey 7296
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135 -------------- ---------- ---------- ----------
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136 Stalker2_I-int LTR Gypsy 12252
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137 -------------- ---------- ---------- ----------
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138 Stalker3_LTR LTR Gypsy 593
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139 -------------- ---------- ---------- ----------
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140 TABOR_I-int LTR Gypsy 3947
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141 -------------- ---------- ---------- ----------
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142 G7_DM LINE Jockey 162
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143 -------------- ---------- ---------- ----------
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144 BEL_I-int LTR Pao 23757
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145 -------------- ---------- ---------- ----------
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146 Gypsy6_I-int LTR Gypsy 7489
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147 ============== ========== ========== ==========
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148
13
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149 Count tables must be generated for each sample individually. Here, edgeR_ is handling a
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150 single factor (genotype, age, treatment, etc) that effect your experiment. This factor has
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151 two levels/states (for instance, "wild-type" and "mutant". You need to select appropriate
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152 count table from your history for each factor level.
0
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153
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154 The following table gives some examples of factors and their levels:
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155
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156 ========= ============== ===============
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157 Factor Factorlevel1 Factorlevel2
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158 --------- -------------- ---------------
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159 Treatment Treated Untreated
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160 --------- -------------- ---------------
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161 Genotype Knockdown Wildtype
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162 --------- -------------- ---------------
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163 TimePoint Day4 Day1
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164 --------- -------------- ---------------
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165 Gender Female Male
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166 ========= ============== ===============
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167
1
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168 *Note*: Output log2 fold changes are based on primary factor level 1 vs. factor level2.
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169 Here the order of factor levels is important. For example, for the factor 'Treatment' given
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170 in above table, edgeR computes fold changes of 'Treated' samples against 'Untreated',
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171 i.e. the values correspond to up or down regulations of genes in Treated samples.
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172
0
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173 **Output**
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174
13
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175 edgeR_ generates a tabular file containing the different columns and results visualized in
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176 a PDF:
0
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177
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178 ====== =============================================================================
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179 Column Description
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180 ------ -----------------------------------------------------------------------------
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181 1 Tag (transposon element ID)
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182 2 the logarithm (to basis 2) of the fold change (See the note in inputs section)
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183 3 p value adjusted for multiple testing with the Benjamini-Hochberg procedure
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184 which controls false discovery rate (FDR)
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185 4 Class the transposon belongs to
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186 5 Type the transposon belongs to
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187 ====== =============================================================================
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188
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189 .. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
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190 ]]>
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191
13
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192 **Note**: This edgeR_ wrapper was adapted from code available at
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193 https://github.com/nskvir/RepEnrich
0
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194
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195 </help>
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196 <citations>
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197 <citation type="doi">10.1093/bioinformatics/btp616</citation>
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198 </citations>
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199 </tool>