annotate masigpro.xml @ 4:402e0b9cfd87 draft default tip

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/masigpro commit 7dc16d5d4169a8fbfb3fad3b2212fd8b6d481f5f"
author iuc
date Sat, 27 Nov 2021 09:58:07 +0000
parents 83f8b5ceff43
children
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1 <!-- TODO remove .1 in tool version with next update -->
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2 <tool id="masigpro" name="maSigPro" version="@TOOL_VERSION@.1+galaxy@VERSION_SUFFIX@">
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3 <description>Significant Gene Expression Profile Differences in Time Course Gene Expression Data</description>
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4 <macros>
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5 <token name="@TOOL_VERSION@">1.49.3</token>
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6 <token name="@VERSION_SUFFIX@">0</token>
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7 </macros>
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8 <xrefs>
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9 <xref type="bio.tools">masigpro</xref>
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10 </xrefs>
1
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11 <requirements>
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12 <requirement type="package" version="8.25">coreutils</requirement>
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13 <requirement type="package" version="@TOOL_VERSION@">bioconductor-masigpro</requirement>
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14 <requirement type="package" version="1.3.2">r-optparse</requirement>
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15 <requirement type="package" version="4.4">sed</requirement>
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16 </requirements>
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17 <stdio>
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18 <regex match="Execution halted"
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19 source="both"
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20 level="fatal"
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21 description="Execution halted." />
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22 <regex match="Error in"
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23 source="both"
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24 level="fatal"
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25 description="An undefined error occurred, please check your input carefully and contact your administrator." />
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26 <regex match="Fatal error"
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27 source="both"
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28 level="fatal"
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29 description="An undefined error occurred, please check your input carefully and contact your administrator." />
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30 </stdio>
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31 <version_command>
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32 <![CDATA[
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33 echo $(R --version | grep version | grep -v GNU)", maSigPro version" $(R --vanilla --slave -e "library(maSigPro); cat(sessionInfo()\$otherPkgs\$maSigPro\$Version)" 2> /dev/null | grep -v -i "WARNING: ")
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34 ]]>
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35 </version_command>
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36 <command>
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37 <![CDATA[
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38 #if str($source.source_selector) == "advanced":
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39 paste
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40 #set $start = True
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41 #set $header = ''
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42 #for $time in $source.rep_time:
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43 #for $file in $time.files:
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44 #if $start:
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45 <(cut -f1 $file)
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46 #set $start = False
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47 #end if
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48 #set $header += ' "' + $file.name + '"'
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49 <(cut -f2 $file)
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50 #end for
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51 #end for
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52 > data && sed -i '1i$header' data &&
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53 #if $source.enable_output:
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54 cp $design_matrix $edesign_out &&
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55 #end if
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56 #set $data = 'data'
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57 #set $edesign = $design_matrix
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58 #else:
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59 #set $data = $source.data
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60 #set $edesign = $source.edesign
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61 #end if
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62 Rscript '${__tool_directory__}/masigpro.R'
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63 -e '$edesign'
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64 -d '$data'
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65 -o '$masigpro_out'
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66 #if str($source.source_selector) == "defaults":
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67 --time_col $source.time_col
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68 --repl_col $source.repl_col
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69 #end if
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70 --degree $makeDesignMatrix.degree
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71 --qvalue $p_vector.qvalue
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72 --min_obs $p_vector.min_obs
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73 --step_method '$Tfit.step_method'
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74 --nvar_correction $Tfit.nvar_correction
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75 --alfa $Tfit.alfa
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76 --rsq $getSiggenes.rsq
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77 --vars '$getSiggenes.vars'
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78 --significant_intercept '$getSiggenes.significant_intercept'
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79 #if $pdf.pdf_selector:
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80 --cluster_data $pdf.seeGenes.clusterData
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81 -k $pdf.seeGenes.k
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82 --print_cluster $pdf.seeGenes.print_cluster
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83 --cluster_method $pdf.seeGenes.clustering.clusterMethod
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84 #if str($pdf.seeGenes.clustering.clusterMethod) == "hclust":
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85 --distance $pdf.seeGenes.clustering.distance
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86 --agglo_method $pdf.seeGenes.clustering.aggloMethod
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87 #end if
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88 #if str($pdf.seeGenes.clustering.clusterMethod) == "kmeans":
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89 --iter_max $pdf.seeGenes.clustering.iterMax
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90 #end if
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91 --color_mode $pdf.seeGenes.colorMode
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92 --show_fit $pdf.seeGenes.showFit
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93 --show_lines $pdf.seeGenes.showLines
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94 --cexlab $pdf.seeGenes.cexlab
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95 --legend $pdf.seeGenes.legend
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96 #end if
3
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97 #if str($source.source_selector) == "advanced" and $source.enable_output
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98 && mv data $data_out
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99 #end if
1
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100 ]]>
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101 </command>
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102 <configfiles>
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103 <configfile name="design_matrix">#if str($source.source_selector) == "advanced":
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104 #set $header = "Name Time Replicate"
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105 #for $group in $source.rep_groups:
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106 #set $header = $header + ' ' + str($group.name)
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107 #end for
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108 $header
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109 #set $c = len($source.rep_repl) + 1
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110 #for $time in $source.rep_time:
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111 #for $file in $time.files:
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112 #set $is_repl = False
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113 #for $i, $repl in enumerate($source.rep_repl):
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114 #if str($file) in str($repl.files):
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115 #set $r = $i + 1
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116 #set $is_repl = True
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117 #end if
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118 #end for
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119 #if $is_repl == False:
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120 #set $r = $c
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121 #set $c += 1
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122 #end if
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123 #set $line = '"' + str($file.name) + '" ' + str($time.time) + ' ' + str($r)
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124 #for $group in $source.rep_groups:
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125 #if str($file) in str($group.files):
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126 #set $line += " 1"
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127 #else
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128 #set $line += " 0"
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129 #end if
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130 #end for
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131 $line
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132 #end for
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133 #end for
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134 #end if
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135 </configfile>
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136 </configfiles>
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137 <inputs>
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138 <conditional name="source">
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139 <param label="Choose data source" name="source_selector"
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140 help="Choose if you want to provide seperate count files (e.g. from HTSeq-count or feature-seq)
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141 and define your experiment design matrix here, or if you have maSigPro edesign and data input files already."
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142 type="select">
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143 <option value="defaults">Use maSigPro edesign and data files</option>
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144 <option value="advanced">Seperate count data (e.g. from HTSeq-count or feature-count)</option>
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145 </param>
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146 <when value="defaults">
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147 <param name="edesign" format="tabular,txt" type="data" label="Experiment matrix"
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148 help="Matrix describing experimental design. Rows must be arrays and columns experiment descriptors" />
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149 <param name="data" format="tabular,txt" type="data" label="Gene expression matrix"
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150 help="Matrix containing normalized gene expression data. Genes must be in rows and arrays in columns" />
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151 <param name="time_col" label="Column number containing time values" type="integer" value="1"
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152 help="Column number in edesign containing time values. Default is first column" />
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153 <param name="repl_col" label="Column number containing replicate coding" type="integer" value="2"
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154 help="Column number in edesign containing coding for replicate arrays. Default is second column" />
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155 </when>
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156 <when value="advanced">
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157 <param name="enable_output" type="boolean" truevalue="1" falsevalue="0" checked="false" label="Output generated maSigPro input files?"
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158 help="Choose if you want to output the generated edesign and data files for direct use in maSigPro as history elements." />
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159 <repeat name="rep_time" title="Time values" min="1" default="1">
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160 <param name="time" type="integer" value="0" label="Specify a numerical time value" help="Only numbers will be allowed">
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161 <sanitizer>
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162 <valid initial="string.digits"></valid>
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163 </sanitizer>
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164 </param>
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165 <param name="files" type="data" format="tabular" multiple="true" label="Counts file(s) at this time value" />
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166 </repeat>
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167 <repeat name="rep_groups" title="Experimental groups" min="1" default="1">
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168 <param name="name" type="text" value="Group title" label="Specify the name of this experimental group"
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169 help="Use a single name without spaces or special characters">
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170 </param>
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171 <param name="files" type="data" format="tabular" multiple="true"
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172 label="Counts file(s) belonging to this experimental group" />
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173 </repeat>
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174 <repeat name="rep_repl" title="Replicates" min="0" default="0">
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175 <param name="files" type="data" format="tabular" multiple="true" label="Counts files that are replicates" />
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176 </repeat>
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177 </when>
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178 </conditional>
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179 <section name="makeDesignMatrix"
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180 title="Step 1: make.Design.Matrix - Defining the regression model"
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181 help="‘make.design.matrix’ creates the design matrix of dummies for
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182 fitting time series micorarray gene expression experiments.">
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183 <param name="degree" type="integer" value="1"
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184 label="Degree of regression fit polynome"
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185 help="The degree of the regression fit polynome. ‘degree’ = 1 returns
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186 linear regression, ‘degree’ = 2 returns quadratic regression, etc" />
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187 </section>
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188 <section name="p_vector"
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189 title="Step 2: p.vector - Finding significant genes"
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190 help="‘p.vector’ performs a regression fit for each gene taking all
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191 variables present in the model given by a regression matrix and
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192 returns a list of FDR corrected significant genes">
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193 <param name="qvalue" type="float" value="0.05" label="Q" help="Significance level" />
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194 <param name="min_obs" label="Minimum values" type="integer" value="6"
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195 help="Genes with less than this number of true numerical values
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196 will be excluded from the analysis. Minimum value to estimate
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197 the model is (degree+1)xGroups+1. Default is 6." />
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198 </section>
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199 <section name="Tfit" title="Step 3: T.fit - Finding significant differences"
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200 help="‘T.fit’ selects the best regression model for each gene using
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201 stepwise regression. In the maSigPro approach ‘p.vector’ and ‘T.fit’ are subsequent
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202 steps, meaning that significant genes are first selected on the
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203 basis of a general model and then the significant variables for
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204 each gene are found by step-wise regression.">
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205 <param name="step_method" type="select" label="Step regression"
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206 help="The step regression can be ‘backward’ or ‘forward’ indicating
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207 whether the step procedure starts from the model with all or none
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208 variables. With the ‘two.ways.backward’ or ‘two.ways.forward’
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209 options the variables are both allowed to get in and out. At each
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210 step the p-value of each variable is computed and variables get
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211 in/out the model when this p-value is lower or higher than given
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212 threshold alfa.">
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213 <option selected="True" value="backward">backward</option>
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214 <option value="forward">forward</option>
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215 <option value="two.ways.backward">two.ways.backward</option>
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216 <option value="two.ways.forward">two.ways.forward</option>
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217 </param>
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218 <param type="boolean" name="nvar_correction" label="nvar correction" truevalue="TRUE" falsevalue="FALSE" checked="false"
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219 help="When nvar.correction is TRUE the given significance
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220 level is corrected by the number of variables in the model.">
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221 <option selected="True" value="FALSE">False</option>
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222 <option value="TRUE">True</option>
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223 </param>
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224 <param name="alfa" type="float" value="0.05" label="alfa" help="Significance level used for variable selection in the stepwise regression" />
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225 </section>
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226 <section name="getSiggenes"
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227 title="Step 4: get.siggenes - Obtaining lists of significant genes"
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228 help="This function creates lists of significant genes for a set of
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229 variables whose significance value has been computed with the
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230 ‘T.fit’ function.">
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231 <param name="rsq" type="float" value="0.7" label="rsq"
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232 help="cut-off level at the R-squared value for the stepwise
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233 regression fit. Only genes with R-squared more than rsq are
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234 selected" />
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235 <param name="vars" type="select" label="Variables"
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236 help="Variables for which to extract significant genes.
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237 ‘all’: generates one single matrix or gene list with all
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238 significant genes.
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239
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240 ‘each’: generates as many significant genes extractions as
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241 variables in the general regression model. Each extraction
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242 contains the significant genes for that variable.
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243
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244 ‘groups’: generates a significant genes extraction for each
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245 experimental group.
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246
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247 The difference between ‘each’ and ‘groups’ is that in the
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248 first case the variables of the same group (e.g. ‘TreatmentA’
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249 and ‘time*TreatmentA’) will be extracted separately and in t
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250 he
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251 second case jointly.">
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252 <option selected="True" value="groups">Groups</option>
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253 <option value="each">Each</option>
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254 <option value="all">All</option>
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255 </param>
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256 <param name="significant_intercept" type="select" label="Significant intercept"
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257 help="The argument ‘significant.intercept’ modulates the treatment for
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258 intercept coefficients to apply for selecting significant genes
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259 when ‘vars’ equals ‘groups’. There are three possible values:
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260 ‘none’, no significant intercept (differences) are considered
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261 for significant gene selection, ‘dummy’, includes genes with
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262 significant intercept differences between control and experimental
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263 groups, and ‘all’ when both significant intercept coefficient
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264 for the control group and significant intercept differences are
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265 considered for selecting significant genes.">
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266 <option selected="True" value="dummy">Dummy</option>
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267 <option value="none">None</option>
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268 <option value="all">All</option>
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269 </param>
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270 </section>
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271 <conditional name="pdf">
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272 <param label="Generate visualization PDF" name="pdf_selector" type="boolean"
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273 truevalue="1" falsevalue="0" checked="true"
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274 help="Choose if you want to generate a PDF file containing the visualizations" />
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275 <when value="1">
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276 <section name="seeGenes" title="Step 5: see.genes - Visualization"
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277 help="This function provides visualisation tools for gene expression
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278 values in a time course experiment. The function first calls the
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279 heatmap function for a general overview of experiment results.
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280 Next a partioning of the data is generated using a clustering
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281 method. The results of the clustering are visualized both as gene
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282 expression profiles extended along all arrays in the experiment,
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283 as provided by the plot.profiles function, and as summary
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284 expression profiles for comparison among experimental groups.">
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285 <param name="clusterData" label="Cluster Data" type="integer" value="1"
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286 help="Data clustering can be done on the basis of either the original
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287 expression values, the regression coefficients, or the t.scores.
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288 In case ‘data’ is a ‘get.siggenes’ object, this is given by
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289 providing the element names of the list
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290 ‘c(sig.profiles,coefficients,t.score)’ of their list
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291 position (1,2 or 3)." />
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292 <param name="k" type="integer" label="Number of clusters for data partioning" value="9" />
2
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293 <param name="print_cluster" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true"
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294 label="Add cluster information to summary file?"
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295 help="Adds columns with the cluster assignment for each gene." />
1
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296 <conditional name="clustering">
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297 <param name="clusterMethod" label="Cluster Method" type="select"
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298 help="clustering method for data partioning. Currently
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299 ‘hclust’, ‘kmeans’ and ‘Mclust’ are supported">
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300 <option selected="True" value="hclust">hclust</option>
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301 <option value="kmeans">kmeans</option>
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302 <option value="Mclust">Mclust</option>
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303 </param>
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304 <when value="hclust">
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305 <param name="distance" type="select" label="Distance measure"
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306 help="Distance measurement function when ‘cluster.method’ is
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307 ‘hclust’. Default uses correlation.">
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308 <option selected="True" value="cor">Correlation</option>
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309 <option value="euclidean">Euclidean</option>
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310 <option value="maximum">Maximum</option>
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311 <option value="manhattan">Manhattan</option>
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312 <option value="Canberra">Canberra</option>
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313 <option value="binary">Binary</option>
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314 <option value="minkowski">Minkowski</option>
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315 </param>
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316 <param name="aggloMethod" type="select" label="Agglomeration method"
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317 help="The agglomeration method to be used when ‘cluster.method’ is ‘hclust’.">
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318 <option selected="True" value="ward.D">ward.D</option>
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319 <option value="ward.D2">ward.D2</option>
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320 <option value="single">single</option>
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321 <option value="complete">complete</option>
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322 <option value="average">average (= UPGMA)</option>
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323 <option value="mcquitty">mcquitty (= WPGMA)</option>
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324 <option value="median">median (= WPGMC)</option>
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325 <option value="centroid">centroid (= UPGMC)</option>
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326 </param>
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327 </when>
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328 <when value="kmeans">
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329 <param name="iterMax" type="integer" label="Maximum number of iterations" value="500"
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330 help="Maximum number of iterations when ‘cluster.method’ is ‘kmeans’" />
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331 </when>
2
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332 <when value="Mclust">
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333 </when>
1
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334 </conditional>
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335 <param name="colorMode" label="Color Mode" type="select" help="Color scale for plotting profiles. Can be either ‘rainbow’ or ‘gray’">
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336 <option selected="True" value="rainbow">Rainbow</option>
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337 <option value="gray">Gray</option>
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338 </param>
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339 <param name="showFit" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Show regression fit curves?"
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340 help="Indicating whether regression fit curves must be plotted" />
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341 <param name="showLines" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Draw lines?"
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342 help="Indicating whether a line must be drawn joining plotted data points for each group" />
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343 <param name="cexlab" type="float" value="0.8" label="Magnification for x labels"
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344 help="Graphical parameter maginfication to be used for x labels in plotting functions" />
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345 <param name="legend" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Add legend to plotting profiles?"
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346 help="Indicating whether legend must be added when plotting profiles" />
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347 </section>
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348 </when>
2
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349 <when value="0">
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350 </when>
1
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351 </conditional>
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352 </inputs>
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353 <outputs>
2
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354 <data format="txt" name="data_out" label="maSigPro data file on ${on_string}">
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355 <filter>
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356 ((
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357 source['source_selector'] == 'advanced' and
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358 source['enable_output'] == True
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359 ))
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360 </filter>
1
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361 </data>
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362 <data format="txt" name="edesign_out" label="maSigPro edesign file on ${on_string}">
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363 <filter>
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364 ((
cc96abdef027 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/masigpro commit c4510bf402d10e8e3a3c4c90c2d96666c987a256
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365 source['source_selector'] == 'advanced' and
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366 source['enable_output'] == True
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367 ))
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368 </filter>
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369 </data>
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370 <data format="pdf" name="pdf_out" from_work_dir="Results.pdf" label="maSigPro Plot file on ${on_string}">
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371 <filter>
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372 ((
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373 pdf['pdf_selector'] == True
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374 ))
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375 </filter>
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376 </data>
2
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377 <data format="tabular" name="masigpro_out" label="maSigPro result file on ${on_string}">
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378 </data>
1
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379 </outputs>
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380 <tests>
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381 <test>
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382 <param name="source_selector" value="advanced" />
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383 <param name="enable_output" value="1" />
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384 <repeat name="rep_time">
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385 <param name="time" value="1" />
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386 <param name="files" value="control_1H.counts,treat_1H.counts" />
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387 </repeat>
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388 <repeat name="rep_time">
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389 <param name="time" value="2" />
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390 <param name="files" value="control_2H.counts,treat_2H.counts" />
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391 </repeat>
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392 <repeat name="rep_time">
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393 <param name="time" value="3" />
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394 <param name="files" value="control_3H.counts,treat_3H_1.counts,treat_3H_2.counts" />
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395 </repeat>
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396 <repeat name="rep_repl">
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397 <param name="files" value="treat_3H_1.counts,treat_3H_2.counts" />
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398 </repeat>
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399 <repeat name="rep_groups">
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400 <param name="name" value="Control" />
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401 <param name="files" value="control_1H.counts,control_2H.counts,control_3H.counts" />
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402 </repeat>
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403 <repeat name="rep_groups">
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404 <param name="name" value="Treatment" />
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405 <param name="files" value="treat_1H.counts,treat_2H.counts,treat_3H_1.counts,treat_3H_2.counts" />
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406 </repeat>
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407 <output name="masigpro_out" file="masigpro_out.tab" />
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408 <output name="data_out" file="data_out.txt" />
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409 <output name="edesign_out" file="edesign_out.txt" />
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410 <output name="pdf_out" file="Results.pdf" />
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411 </test>
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412 <test>
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413 <param name="source_selector" value="defaults" />
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414 <param name="edesign" value="edesign_out.txt" />
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415 <param name="data" value="data_out.txt" />
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416 <output name="masigpro_out" file="masigpro_out.tab" />
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417 <output name="pdf_out" file="Results.pdf" />
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418 </test>
2
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419 <test>
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420 <param name="source_selector" value="defaults" />
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421 <param name="edesign" value="edesign_out.txt" />
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422 <param name="data" value="data_out.txt" />
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423 <param name="print_cluster" value="FALSE" />
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424 <output name="masigpro_out" file="masigpro_out_no_cluster.tab" />
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425 <output name="pdf_out" file="Results.pdf" />
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426 </test>
1
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427 </tests>
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428 <help>
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429 <![CDATA[
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430 .. class:: infomark
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431
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432 **What it does**
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433
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434 maSigPro_ is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray and RNA-Seq experiments.
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435
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436 **Inputs**
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437
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438 The maSigPro wrapper has two options for input data:
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439
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440 - directly through two seperate text files containing the experiment design (edesign) and the data or
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441 - count tables generated from HTSeq-count. Count tables must be generated for each sample individually.
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442
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443 To set up an experimental design from seperate count files you first have to select which files belong to a certain time point.
cc96abdef027 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/masigpro commit c4510bf402d10e8e3a3c4c90c2d96666c987a256
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444 Likewise you can specify which files are replicates. In a third step you have to create the experimental groups and select the related files.
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445 For a more comfortable setup in future analysis you have the option to output the generated edesign and data files.
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446
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447 **Output**
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448
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449 maSigPro_ generates a summary file containing the list of significant genes. Additionally you can obtain a PDF file containing plots of profiles and groups that visualize the clustering analysis.
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450
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451 .. _maSigPro: https://bioconductor.org/packages/release/bioc/html/maSigPro.html
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452 ]]>
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453 </help>
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454 <citations>
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455 <citation type="doi">10.1093/bioinformatics/btl056</citation>
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456 </citations>
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457 </tool>