annotate hairpinTool.xml @ 16:525bf4364896

- Fixed sample reads filter statistics a bit more
author shian_su <registertonysu@gmail.com>
date Mon, 12 Jan 2015 16:35:08 +1100
parents 5a917ea5bed2
children 438f2733bc27
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1 <tool id="shRNAseq" name="shRNAseq Tool" version="1.2.1">
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2 <description>
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3 Analyse differential representation for shRNAseq and sgRNA based procedures
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4 using edgeR package from Bioconductor.
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5 </description>
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6
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7 <requirements>
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8 <requirement type="R-module" version="3.7.17">edgeR</requirement>
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9 <requirement type="R-module" version="3.21.16">limma</requirement>
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10 <requirement type="package" version="3.1.1">R_3_0_3</requirement>
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11 </requirements>
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12
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13 <stdio>
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14 <exit_code range="1:" level="fatal" description="Tool exception" />
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15 </stdio>
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17 <command interpreter="Rscript">
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18 hairpinTool.R $inputOpt.inputType
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19 #if $inputOpt.inputType=="fastq":
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20
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21 #for $i, $fas in enumerate($inputOpt.fastq):
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22 fastq::$fas.file
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23 #end for
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24
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25 $inputOpt.hairpin
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26 $inputOpt.samples
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27
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28 #if $inputOpt.positions.posOption=="yes":
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29 $inputOpt.positions.barstart
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30 $inputOpt.positions.barend
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31 0
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32 0
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33 $inputOpt.positions.hpstart
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34 $inputOpt.positions.hpend
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35 #else:
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36 1
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37 5
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40 37
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41 57
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42 #end if
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43 #elif $inputOpt.inputType=="pairedFastq":
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44
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45 #for $i, $fas in enumerate($inputOpt.fastq):
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46 fastq::$fas.file
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47 #end for
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48
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49 #for $i, $fas in enumerate($inputOpt.fastq):
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50 fastqRev::$fas.fileRev
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51 #end for
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52
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53 $inputOpt.hairpin
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54 $inputOpt.samples
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55
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56 #if $inputOpt.positions.posOption=="yes":
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57 $inputOpt.positions.barstart
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58 $inputOpt.positions.barend
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59 $inputOpt.positions.barstartRev
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60 $inputOpt.positions.barendRev
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61 $inputOpt.positions.hpstart
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62 $inputOpt.positions.hpend
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63 #else:
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64 1
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65 5
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66 0
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67 0
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69 57
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70 #end if
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71
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72 #elif $inputOpt.inputType=="counts":
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73 $inputOpt.counts
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74 $inputOpt.hairpin
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75 $inputOpt.samples
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76 0
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80 0
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81 #end if
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82
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83 #if $inputOpt.secondaryFactor.secFactorOpt=="yes":
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84 "$inputOpt.secondaryFactor.secFactName"
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85 #else:
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86 "none"
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87 #end if
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88
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89 #if $filterCPM.filtOption=="yes":
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90 $filterCPM.cpmReq
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91 $filterCPM.sampleReq
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92 $filterCPM.readReq
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93 #else:
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94 -Inf
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95 -Inf
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96 -Inf
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97 #end if
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98
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99 "$fdr"
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100 "$lfc"
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101 "$direction"
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102 "$workMode.mode"
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103 "$outFile"
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104 "$outFile.files_path"
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105
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106 #if $workMode.mode=="classic":
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107 "$workMode.pair1"
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108 "$workMode.pair2"
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109 #elif $workMode.mode=="glm":
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110 "$workMode.contrast"
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111 "$workMode.roast.roastOption"
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112
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113 #if $workMode.roast.roastOption=="yes":
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114 "$workMode.roast.hairpinReq"
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115 "$workMode.roast.select.selOption"
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116 "$workMode.roast.select.selection"
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117 #else:
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118 0
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119 0
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120 0
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121 #end if
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122
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123 #end if
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124 </command>
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125
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126 <inputs>
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127 <conditional name="inputOpt">
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128
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129 <param name="inputType" type="select" label="Input File Type">
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130 <option value="fastq">FastQ File</option>
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131 <option value="pairedFastq">Paired FastQ File</option>
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132 <option value="counts">Table of Counts</option>
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133 </param>
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134
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135 <when value="fastq">
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136 <param name="hairpin" type="data" format="tabular"
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137 label="Target Annotation"/>
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138
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139 <param name="samples" type="data" format="tabular"
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140 label="Sample Annotation"/>
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141
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142 <repeat name="fastq" title="FastQ Files">
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143 <param name="file" type="data" format="fastq"/>
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144 </repeat>
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145
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146 <conditional name="secondaryFactor">
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147
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148 <param name="secFactorOpt" type="select"
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149 label="Include Secondary Factor">
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150
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151 <option value="no" selected="True">No</option>
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152
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153 <option value="yes">Yes</option>
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154
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155 </param>
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156
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157 <when value="yes">
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158
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159 <param name="secFactName" type="text" label="Secondary Factor Name"
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160 size="80"/>
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161
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162 </when>
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163
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164 <when value="no">
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165 </when>
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166 </conditional>
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167
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168 <conditional name="positions">
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169 <param name="posOption" type="select"
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170 label="Specify Sample Index and Target Sequence Locations?"
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171 help="Default Positions: Index: 1 to 5, Target: 37 to 57.">
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172 <option value="no" selected="True">No</option>
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173 <option value="yes">Yes</option>
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174 </param>
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175
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176 <when value="yes">
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177 <param name="barstart" type="integer" value="1"
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178 label="Index Starting Position"/>
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179 <param name="barend" type="integer" value="5"
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180 label="Index Ending Position"/>
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181
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182 <param name="hpstart" type="integer" value="37"
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183 label="Target Starting Position"/>
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184
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185 <param name="hpend" type="integer" value="57"
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186 label="Target Ending Position"/>
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187 </when>
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188
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189 <when value="no"/>
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190 </conditional>
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191 </when>
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192
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193 <when value="pairedFastq">
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194 <param name="hairpin" type="data" format="tabular"
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195 label="Target Sequence Annotation"/>
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196
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197 <param name="samples" type="data" format="tabular"
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198 label="Sample Annotation"/>
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199
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200 <repeat name="fastq" title="FastQ Files">
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201 <param name="file" type="data" format="fastq"/>
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202 <param name="fileRev" type="data" format="fastq"/>
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203 </repeat>
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204
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205 <conditional name="secondaryFactor">
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206
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207 <param name="secFactorOpt" type="select"
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208 label="Include Secondary Factor">
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209
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210 <option value="no" selected="True">No</option>
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211
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212 <option value="yes">Yes</option>
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213
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214 </param>
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215
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216 <when value="yes">
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217
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218 <param name="secFactName" type="text" label="Secondary Factor Name"
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219 size="80"/>
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220
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221 </when>
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222
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223 <when value="no">
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224 </when>
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225 </conditional>
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226
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227 <conditional name="positions">
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228
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229 <param name="posOption" type="select"
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230 label="Specify Sample Index and Target Sequence Locations?"
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231 help="Default Positions: Index: 1 to 5, Input required for
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232 reverse end, Target: 37 to 57.">
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233
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234 <option value="no" selected="True">No</option>
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235
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236 <option value="yes">Yes</option>
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237
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238 </param>
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239
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240 <when value="yes">
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241 <param name="barstart" type="integer" value="1"
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242 label="Index Starting Position"/>
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243
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244 <param name="barend" type="integer" value="5"
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245 label="Index Ending Position"/>
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246
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247 <param name="barstartRev" type="integer" value="0"
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248 label="Reverse Index Starting Position"/>
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249
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250 <param name="barendRev" type="integer" value="0"
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251 label="Reverse Index Ending Position"/>
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252
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253 <param name="hpstart" type="integer" value="37"
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254 label="Target Starting Position"/>
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255
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256 <param name="hpend" type="integer" value="57"
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257 label="Target Ending Position"/>
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258 </when>
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259
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260 <when value="no">
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261 </when>
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262
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263 </conditional>
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264
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265 </when>
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266
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267 <when value="counts">
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268
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269 <param name="counts" type="data" format="tabular" label="Counts Table"/>
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270
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271 <param name="hairpin" type="data" format="tabular"
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272 label="Target Sequence Annotation"/>
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273
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274 <param name="samples" type="data" format="tabular"
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275 label="Sample Annotation"/>
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276
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277 <conditional name="secondaryFactor">
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278
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279 <param name="secFactorOpt" type="select"
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280 label="Include Secondary Factor">
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281
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282 <option value="no" selected="True">No</option>
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283
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284 <option value="yes">Yes</option>
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285
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286 </param>
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287
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288 <when value="yes">
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289
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290 <param name="secFactName" type="text" label="Secondary Factor Name"
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291 size="80"/>
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292
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293 </when>
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294
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295 <when value="no">
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296 </when>
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297
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298 </conditional>
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299
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300 </when>
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301
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302 </conditional>
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303
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304 <conditional name="filterCPM">
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305 <param name="filtOption" type="select" label="Filter Low CPM?"
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306 help="Ignore target sequences with very low representation when
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307 performing analysis.">
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308 <option value="yes">Yes</option>
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309 <option value="no">No</option>
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310 </param>
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311
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312 <when value="yes">
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313 <param name="cpmReq" type="float" value="0.5" min="0"
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314 label="Minimum CPM"/>
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315
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316 <param name="sampleReq" type="integer" value="1" min="0"
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317 label="Minimum Samples"
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318 help="Filter out all the genes that do not meet the minimum
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319 CPM in at least this many samples."/>
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320
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321 <param name="readReq" type="integer" value="1000" min="0"
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322 label="Minimum Reads"
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323 help="Filter out all samples that do not have the minimum
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324 number of reads."/>
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325
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326 </when>
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327
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328 <when value="no"/>
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329
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330 </conditional>
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331
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332 <conditional name="workMode">
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333 <param name="mode" type="select" label="Analysis Type"
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334 help="Classic Exact Tests are useful for simple comparisons across
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335 two sampling groups. Generalised linear models allow for more
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336 complex contrasts and gene level analysis to be made.">
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337 <option value="classic">Classic Exact Test</option>
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338 <option value="glm">Generalised Linear Model</option>
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339 </param>
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340
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341 <when value="classic">
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342 <param name="pair1" type="text" label="Compare" size="40"/>
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343 <param name="pair2" type="text" label="To" size="40"
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344 help="The analysis will subtract values of this group from those
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345 in the group above to establish the difference."/>
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346 </when>
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347
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348 <when value="glm">
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349 <param name="contrast" type="text" size="60"
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350 label="Contrasts of interest"
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351 help="Specify equations defining contrasts to be made. Eg.
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352 KD-Control will result in positive fold change if KD has
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353 greater expression and negative if Control has greater
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354 expression."/>
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355
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356 <conditional name="roast">
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357 <param name="roastOption" type="select"
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358 label="Perform Gene Level Analysis?"
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359 help="Analyse LogFC tendencies for target sequences belonging
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360 to the same gene. NOTE: this is a slow procedure that
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361 scales badly with the number of genes analysed.">
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362 <option value="no">No</option>
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363 <option value="yes">Yes</option>
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364 </param>
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365
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366 <when value="yes">
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367 <param name="hairpinReq" type="integer" value="2" min="2"
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368 label="Minimum Targets Found"
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369 help="Only genes with at least this many target sequences
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370 found will be analysed."/>
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371
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372 <conditional name="select">
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373 <param name="selOption" type="select"
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374 label="Gene Selection Method">
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375 <option value="rank">By p-value Rank</option>
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376 <option value="geneID">By Gene Identifier</option>
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377 </param>
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378 <when value="rank">
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379 <param name="selection" type="text" size="40" value="1:5"
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380 label="Ranks of Top Genes to Plot"
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381 help="Genes are ranked in ascending p-value for
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382 differential representation, individual ranks can
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383 be entered seperated by comma or a range seperated
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384 by colon."/>
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385 </when>
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386 <when value="geneID">
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387 <param name="selection" type="text" size="80" value=""
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388 label="Symbols of Genes to Plot"
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389 help="Select genes based on their identifier in the
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390 'Gene' column of the sample information file.
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391 Please ensure exact match with the values in input
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392 file and separate selections with commas."/>
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393 </when>
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394 </conditional>
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395
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396
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397 </when>
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398
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399 <when value="no"/>
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400 </conditional>
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401 </when>
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402 </conditional>
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403
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404 <param name="fdr" type="float" value="0.05" min="0" max="1"
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405 label="FDR Threshold"
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406 help="All observations below this threshold will be highlighted
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407 in the smear plot."/>
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408
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409 <param name="lfc" type="float" value="0" min="0"
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410 label="Absolute LogFC Threshold"
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411 help="In additional to meeting the FDR requirement, the absolute
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412 value of the log-fold-change of the observation must be above
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413 this threshold to be highlighted."/>
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414
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415 <param name="direction" type="select" label="Highlight Option"
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416 help="Only hightlight positive or negative fold changes in smear plot?">
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417 <option value="all">Default</option>
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418 <option value="up">Positive Only</option>
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419 <option value="down">Negative Only</option>
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420 </param>
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421 </inputs>
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422
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423 <outputs>
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424 <data format="html" name="outFile" label="TagSeq Analysis"/>
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425 </outputs>
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426 <help>
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427 .. class:: infomark
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428
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429 **What it does**
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430
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431 Given tables containing information about the hairpins/sgRNA and their
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432 associated sample indices, information about the samples and fastq file
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433 containing the sequencing reads. This tool will generate plots and tables for
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434 the analysis of differential representation.
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435
7
91e411fcdecc Version 1.0.8
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436 .. class:: infomark
91e411fcdecc Version 1.0.8
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437
91e411fcdecc Version 1.0.8
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438 A tutorial of how to use this tool is available at:
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439 http://bioinf.wehi.edu.au/shRNAseq/galaxy.html
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440
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441 -----
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442
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443 .. class:: infomark
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444
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445 **INPUTS**
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446
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447 **Input File Type:**
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448
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449 This tool is able to either generate counts from a raw FastQ file given the
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450 information regarding the samples and hairpins/sgRNA. Alternatively if a table
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451 of counts has already been generated it can also be used.
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452
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453 **Counts Table (Counts Input):**
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454
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455 A tab delimited text table of information regarding the counts of
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456 hairpins/sgRNA. Should have a column 'ID' to denote the hairpins/sgRNA that
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457 counts correspond to. Each additional column should have titles corresponding to
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458 the label for the sample.
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459
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460 Example::
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461
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462 ID Sample1 Sample2 Sample3
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463 Control1 49802 48014 40148
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464 Control2 12441 16352 14232
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465 Control3 9842 9148 9111
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466 Hairpin1 3300 3418 2914
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467 Hairpin2 91418 95812 93174
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468 Hairpin3 32985 31975 35104
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469 Hairpin4 12082 14081 14981
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470 Hairpin5 2491 2769 2691
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471 Hairpin6 1294 1486 1642
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472 Hairpin7 49501 49076 47611
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473 ...
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474
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475 **Target Sequence Annotation:**
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476
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477 A tab delimited text table of information regarding the targetted
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478 hairpins/sgRNA sequence. Should have columns 'ID', 'Sequences' and 'Gene' to
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479 uniquely identify the target, align it with the reads to produce counts and
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480 identify which gene the target acts on.
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481
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482 NOTE: the column names are case sensitive and should be input exactly as they
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483 are shown here.
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484
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485 Example::
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486
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487 ID Sequences Gene
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488 Control1 TCTCGCTTGGGCGAGAGTAAG 2
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489 Control2 CCGCCTGAAGTCTCTGATTAA 2
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490 Control3 AGGAATTATAATGCTTATCTA 2
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491 Hairpin1 AAGGCAGAGACTGACCACCTA 4
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492 Hairpin2 GAGCGACCTGGTGTTACTCTA 4
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493 Hairpin3 ATGGTGTAAATAGAGCTGTTA 4
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494 Hairpin4 CAGCTCATCTTCTGTGAAGAA 4
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495 Hairpin5 CAGCTCTGTGGGTCAGAAGAA 4
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496 Hairpin6 CCAGGCACAGATCTCAAGATA 4
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497 Hairpin7 ATGACAAGAAAGACATCTCAA 7
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498 ...
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499
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500 **Sample Annotation (FastQ Input):**
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501
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502 A tab delimited text table of information regarding the samples. Should have
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503 columns 'ID', 'Sequences' and 'group' to uniquely identify each sample, identify
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504 the sample in the reads by its sample index sequence and correctly group
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505 replicates for analysis. Additional columns may inserted for annotation purposes
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506 and will not interfere with analysis as long as the necessary columns are
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507 present.
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508
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509 NOTE: With the exception of other_group, column names are case sensitive and
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510 should be input exactly as they are shown here. The other_group column can be
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511 named by the user and specified in the "Include Secondary Factor" option of the
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512 tool.
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513
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514 Example::
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515
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516 ID Sequences group other_group Replicate
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517 3 GAAAG Day 2 male 1
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518 6 GAACC Day 10 female 1
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519 9 GAAGA Day 5 GFP neg male 1
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520 16 GAATT Day 5 GFP pos male 1
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521 18 GACAC Day 2 female 2
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522 21 GACCA Day 10 male 2
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523 28 GACGT Day 5 GFP neg male 2
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524 31 GACTG Day 5 GFP pos female 2
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525 33 GAGAA Day 2 male 3
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526 40 GAGCT Day 10 female 3
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527 ...
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528
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529 **Include Secondary Factor**
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530 If there are two factors involved in the experiment (i.e. Age and Gender) then
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531 then secondary factor should be included to improve the statistical analysis.
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532 The secondary factor should be specified as a column in the sample annotation
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533 file and the corresponding column name should be input exactly as it is into
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534 the provided field in the tool.
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535
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536 NOTE: Currently the secondary factor is used only to improve statistical
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537 analysis, comparisons can only be made in the primary factor specified as
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538 "group" in the sample annotation.
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539
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540 **Specify Sample Index and Target Sequence Locations (FastQ Input):**
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541
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542 It is assumed that in the sequencing reads that the first 5 bases are the
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543 sample index sequence and that bases 37-57 are the hairpins/sgRNA. If this is
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544 not the case then the values of the positions can be changed, however it still
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545 requires the sample indices and hairpins/sgRNA to be in a consistent location an
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546 in a continuous sequence.
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547
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548 NOTE: position values start at 1 for the first base.
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549
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550 **Filter Low CPM?:**
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551
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552 Often in a large screen there may members with very low counts which are of no
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553 interest in the experiment, these may be filtered out to speed up computations.
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554 Filtering will be based on counts per million in a required number of samples.
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555
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556 **Analysis Type:**
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557
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558 * **Classic Exact Test:** This allows two experimental groups to be compared
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559 and p-values for differential representation derivec for each target
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560 sequence. Simple and fast for straightforward comparisons. In this option you
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561 will have the option of "*Compare* x *To* y" which implicitly subtracts the
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562 data from y from that of x to produce the comparison.
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563
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564 * **Generalised Linear Model:** This allow for complex contrasts to be specified
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565 and also gene level analysis to be performed. If this option is chosen then
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566 contrasts must be explicitly stated in equations and multiple contrasts can
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567 be made. In addition there will be the option to analyse hairpins/sgRNA on a
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568 per-gene basis to see if hairpins/sgRNA belonging to a particular gene have
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569 any overall tendencies for the direction of their log-fold-change.
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570
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571 **FDR Threshold:**
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572 The smear plot in the output will have hairpins/sgRNA highlighted to signify
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573 significant differential representation. The significance is determined by
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574 contorlling the false discovery rate, only those with a FDR lower than the
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575 threshold will be highlighted in the plot.
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576
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577 -----
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578
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579 **Citations:**
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580
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581 .. class:: infomark
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582
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583 limma
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584
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585 Please cite the paper below for the limma software itself. Please also try
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586 to cite the appropriate methodology articles that describe the statistical
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587 methods implemented in limma, depending on which limma functions you are
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588 using. The methodology articles are listed in Section 2.1 of the limma
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589 User's Guide.
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590
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591 * Smyth, GK (2005). Limma: linear models for microarray data. In:
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592 'Bioinformatics and Computational Biology Solutions using R and
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593 Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry,
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594 W. Huber (eds), Springer, New York, pages 397-420.
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595
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596 .. class:: infomark
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597
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598 edgeR
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599
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600 Please cite the first paper for the software itself and the other papers for
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601 the various original statistical methods implemented in edgeR. See
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602 Section 1.2 in the User's Guide for more detail.
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603
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604 * Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor
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605 package for differential expression analysis of digital gene expression
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606 data. Bioinformatics 26, 139-140
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607
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608 * Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing
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609 differences in tag abundance. Bioinformatics 23, 2881-2887
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610
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611 * Robinson MD and Smyth GK (2008). Small-sample estimation of negative
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612 binomial dispersion, with applications to SAGE data.
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613 Biostatistics, 9, 321-332
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614
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615 * McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis
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616 of multifactor RNA-Seq experiments with respect to biological variation.
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617 Nucleic Acids Research 40, 4288-4297
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618
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548802b3492f Version 1.0.9
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619 Report problems to: su.s@wehi.edu.au
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620
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621 .. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
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622 .. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html
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623 </help>
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624 </tool>