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1 <tool id="bwbinavg" name="bigwig summary">
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2 <description>for intervals</description>
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3 <command interpreter="python">getGenomicScore.py $input $output $score_type $bwfile $nbin $strand $outplot $span</command>
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4 <inputs>
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5 <param name="input" format="interval" type="data" label="Interval file"/>
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6 <param name="bwfile" format="bigwig" type="data" label="BigWig file"/>
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7 <param name="score_type" type="select" label="Select score summary type" >
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8 <option value="mean" selected="true">mean</option>
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9 <option value="max">maximum</option>
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10 <option value="min">minimum</option>
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11 <option value="std">standard deviation</option>
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12 <option value="coverage">coverage:fraction covered</option>
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13 </param>
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14 <param name="nbin" type="integer" value="1" label="number of bins"/>
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15 <param name="strand" type="integer" value="0" label="Specify the strand column" help="leave 0 to ignore strand information. Only matters if using more than 1 bin"/>
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16 <param name="span" size="10" type="float" value="0.1" label="loess span: smoothing parameter" help="value less then 0.1 disables smoothing"/>
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17 </inputs>
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18 <outputs>
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19 <data format="pdf" name="outplot" label="${tool.name} on ${on_string}[plot]"/>
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20 <data format="interval" name="output" label="${tool.name} on ${on_string}[data]"/>
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21 </outputs>
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22 <help>
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23
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24 .. class:: infomark
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25
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26 Each interval is binned and the average base-resolution score/coverage/density in the bigwig file is added as new columns appended at the end of the original file .
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27
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28 **Example**
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29
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30 If your original data has the following format:
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31
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32 +-----+-----+---+------+
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33 |chrom|start|end|other2|
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34 +-----+-----+---+------+
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35
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36 and you choose to divide each interval into 3 bins and return the mean scores of each bin, your output will look like this:
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37
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38 +-----+-----+---+------+-----+-----+-----+
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39 |chrom|start|end|other2|mean1|mean2|mean3|
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40 +-----+-----+---+------+-----+-----+-----+
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41
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42
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43 </help>
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44 </tool>
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