<tool id="DimontPredictor" name="DimontPredictor" version="0.1" force_history_refresh="true">
<description>for predicting binding sites using a Dimont model</description>
<command>java -Xms256M -Xmx2G -jar \$JAR_PATH/DimontPredictorWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path</command>
<inputs>
<param type="text" size="40" name="DimontPredictor_jobname" label="Job name" value="" optional="true" help="Please enter a name for your job that should be used in the history (optional)">
</param>
<param type="data" format="xml" name="DimontPredictor_ps_Dimont" label="&lt;hr /&gt;Dimont" help="The trained Dimont classifier, i.e. the &quot;Dimont&quot; output of a previous Dimont run." value="" optional="false">
</param>

<param type="data" format="fasta" name="DimontPredictor_ps_Input_sequences" label="&lt;hr /&gt;Input sequences" help="The input sequences for de-novo motif discovery (can be uploaded using &quot;GetData&quot; -&gt; &quot;Upload File&quot;), annotated FastA format. The required format is described in the help section." value="" optional="false">
</param>

<param type="text" size="40" name="DimontPredictor_ps_Value_tag" label="Value tag" help="The tag for the value information in the FastA-annotation of the input file" value="" optional="false">
</param>

<param type="text" size="40" name="DimontPredictor_ps_Weighting_factor" label="Weighting factor" help="The value for weighting the data; either a value between 0 and 1, or a description relative to the standard deviation (e.g. +4sd)" value="0.2" optional="false">
</param>

<param type="float" name="DimontPredictor_ps_p_value" label="&lt;hr /&gt;p-value" help="The maximum p-value allowed for predicted binding sites" value="0.0010" optional="false">
<validator type="in_range" min="0.0" max="1.0" message="Value is not in the specified range [0.0, 1.0]."/></param>

</inputs>
<requirements>
	<requirement type="set_environment">JAR_PATH</requirement>
	<requirement type="binary" version=">=1.6">java</requirement>
</requirements>
<configfiles>
<configfile name="script_file">
&lt;DimontPredictor_ps_Dimont&gt;
&lt;value&gt;
${DimontPredictor_ps_Dimont}&lt;/value&gt;
&lt;extension&gt;
${DimontPredictor_ps_Dimont.ext}&lt;/extension&gt;
&lt;/DimontPredictor_ps_Dimont&gt;

&lt;DimontPredictor_ps_Input_sequences&gt;
&lt;value&gt;
${DimontPredictor_ps_Input_sequences}&lt;/value&gt;
&lt;extension&gt;
${DimontPredictor_ps_Input_sequences.ext}&lt;/extension&gt;
&lt;/DimontPredictor_ps_Input_sequences&gt;

&lt;DimontPredictor_ps_Value_tag&gt;
${DimontPredictor_ps_Value_tag}&lt;/DimontPredictor_ps_Value_tag&gt;

&lt;DimontPredictor_ps_Weighting_factor&gt;
${DimontPredictor_ps_Weighting_factor}&lt;/DimontPredictor_ps_Weighting_factor&gt;

&lt;DimontPredictor_ps_p_value&gt;
${DimontPredictor_ps_p_value}&lt;/DimontPredictor_ps_p_value&gt;

</configfile>
</configfiles>
<outputs>
<data format="html" name="summary" label="#if str($DimontPredictor_jobname) == '' then $tool.name + ' on ' + $on_string else $DimontPredictor_jobname#">
</data>
</outputs>
<tests>
 <test>
 	<param name="DimontPredictor_jobname" value="Test" />
	<param name="DimontPredictor_ps_Dimont" value="predictor_test.xml" ftype="xml" />
	<param name="DimontPredictor_ps_Input_sequences" value="dimont_test.fasta" />
	<param name="DimontPredictor_ps_Value_tag" label="Value tag" value="maxT" />
	<param name="DimontPredictor_ps_Weighting_factor" value="0.2" />
	<param name="DimontPredictor_ps_p_value" value="0.0010" />
	<output name="summary" file="TestPred/TestPred_html.html" />
 </test>
</tests>
<help>
**DimontPredictor** allows for predicting binding sites in new data using a previously trained Dimont model. For training a Dimont model see tool "Dimont".

This tool may be useful if you, for instance, want to predict binding sites of a previously discovered motifs in other data sets, or if you want to try different p-values for filtering predictions.

Input sequences must be supplied in an annotated FastA format as a file uploaded by the "Upload File" task in section "Get Data" of Galaxy or generated using the "Dimont Data Extractor" tool.
In the annotation of each sequence, you need to provide a value that reflects the confidence that this sequence is bound by the factor of interest.
Such confidences may be peak statistics (e.g., number of fragments under a peak) for ChIP data or signal intensities for PBM data.

For instance, an annotated FastA file for ChIP-exo data could look like::
	
	> signal: 515
	ggccatgtgtatttttttaaatttccac...
	> signal: 199
	GGTCCCCTGGGAGGATGGGGACGTGCTG...
	...

where the confidence for the first two sequences amounts to 515 and 199, respectively.
The FastA comment may contain additional annotations of the format ``key1 : value1; key2: value2;...``.
We also provide an example_ input file.

Accordingly, you would need to set the parameter "Value tag" to ``signal`` for this input file.

The parameter "Weighting factor" defines the proportion of sequences that you expect to be bound by the targeted factor with high confidence. For ChIP data, the default value of ``0.2`` typically works well. 
For PBM data, containing a large number of unspecific probes, this parameter should be set to a lower value, e.g. ``0.01``.

The parameter "p-value" defines a threshold on the p-values of predicted binding sites, and only binding sites with a lower p-value are reported by DimontPredictor.
The Dimont tool uses a p-value threshold of ``1E-3``, which is also the default value of DimontPredictor.

You can also install this web-application within your local Galaxy server. Instructions can be found at the Dimont_ page of Jstacs. 
There you can also download a command line version of DimontPredictor.

If you experience problems using DimontPredictor, please contact_ us.

.. _example: http://www.jstacs.de/downloads/dimont-example.fa
.. _Dimont: http://jstacs.de/index.php/Dimont
.. _contact: mailto:grau@informatik.uni-halle.de
</help>
</tool>