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1 <tool id="metaMA" name="MetaMA" version="0.1.0">
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2 <description>metaMA wrapper</description>
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3 <requirements>
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4 <container type="docker">sblanck/testtool:latest</container>
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5 </requirements>
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6 <command>
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7
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8 /galaxy-tools/stderr_wrapper.py Rscript
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9 /galaxy-tools/transcriptomics/MetaMA/MetaMA.R
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10 #for $currentInput in $inputList
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11 "${currentInput.rdataset}"
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12 "${currentInput.selectCondition}"
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13 #end for
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14 $result_html
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15 $result_html.extra_files_path
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16 /galaxy-tools/transcriptomics/MetaMA/MetaMa_tpl.html
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17 </command>
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18
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19 <inputs>
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20
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21 <repeat name="inputList" title="Datasets">
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22 <param name="rdataset" type="data" format="rdata" label="RData" help="RData to be used"/>
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23
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24 <param name="conditions" type="data" format="cond" label="Conditions" help="conditions associated with the rData file"/>
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25
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26 <param name="selectCondition" type="select" label="tumor condition">
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27 <options from_dataset="conditions">
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28 <column name="name" index="0"/>
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29 <column name="value" index="0"/>
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30 </options>
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31 </param>
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32
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33
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34
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35 </repeat>
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36
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37 </inputs>
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38 <outputs>
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39 <data format="html" name="result_html" label="Annotations"/>
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40 </outputs>
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41
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42 <help>
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43 NOTE: This metaMA wrapper performs p-value combination from multiples studies with the same probes. If you need to normalize your data, use "matrix_normalisation" tool on each file. Then, use "Merge Standard datasets(copied)" tool to make a multiple file dataset.
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44 </help>
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45
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46 </tool>
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