# HG changeset patch
# User grau
# Date 1383753897 18000
# Node ID 93f3b1563fa6195d33f04bad96bbbe153ce236cd
# Parent  38383332b553832bbdd32778936fc3153456e105
Uploaded

diff -r 38383332b553 -r 93f3b1563fa6 DimontWeb.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/DimontWeb.xml	Wed Nov 06 11:04:57 2013 -0500
@@ -0,0 +1,134 @@
+<tool id="Dimont" name="Dimont" version="0.1" force_history_refresh="true">
+<description>Dimont, a universal tool for de-novo motif discovery (beta).</description>
+<command>java -Xms256M -Xmx2G -jar /Users/dev/Desktop/ChIP-seq/galaxy/DimontWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path</command>
+<inputs>
+<param type="text" size="40" name="Dimont_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="fasta" name="Dimont_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="Dimont_ps_Position_tag" label="Position tag" help="The tag for the position information in the FastA-annotation of the input file" value="" optional="false">
+</param>
+
+<param type="text" size="40" name="Dimont_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="float" name="Dimont_ps_Standard_deviation" label="Standard deviation" help="The standard deviation of the position distribution centered at the position specified by the position tag" value="75.0" optional="false">
+<validator type="in_range" min="1.0" max="10000.0" message="Value is not in the specified range [1.0, 10000.0]."/></param>
+
+<param type="text" size="40" name="Dimont_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="integer" name="Dimont_ps_Starts" label="&lt;hr /&gt;Starts" help="The number of pre-optimization runs." value="20" optional="false">
+<validator type="in_range" min="1" max="100" message="Value is not in the specified range [1, 100]."/></param>
+
+<param type="integer" name="Dimont_ps_Initial_motif_width" label="&lt;hr /&gt;Initial motif width" help="The motif width that is used initially, may be adjusted during optimization." value="15" optional="false">
+<validator type="in_range" min="1" max="50" message="Value is not in the specified range [1, 50]."/></param>
+
+<param type="integer" name="Dimont_ps_Markov_order_of_motif_model" label="Markov order of motif model" help="The Markov order of the model for the motif." value="0" optional="false">
+<validator type="in_range" min="0" max="3" message="Value is not in the specified range [0, 3]."/></param>
+
+<param type="integer" name="Dimont_ps_Markov_order_of_background_model" label="Markov order of background model" help="The Markov order of the model for the background sequence and the background sequence, -1 defines uniform distribution." value="-1" optional="false">
+<validator type="in_range" min="-1" max="5" message="Value is not in the specified range [-1, 5]."/></param>
+
+<param type="float" name="Dimont_ps_Equivalent_sample_size" label="&lt;hr /&gt;Equivalent sample size" help="Reflects the strength of the prior on the model parameters." value="4.0" optional="false">
+<validator type="in_range" min="0.0" max="Infinity" message="Value is not in the specified range [0.0, Infinity]."/></param>
+
+<param type="boolean" name="Dimont_ps_Delete_BSs_from_profile" label="Delete BSs from profile" help="A switch for deleting binding site positions of discovered motifs from the profile before searching for futher motifs." checked="True" optional="false">
+</param>
+
+</inputs>
+<configfiles>
+<configfile name="script_file">
+&lt;Dimont_ps_Input_sequences&gt;
+&lt;value&gt;
+${Dimont_ps_Input_sequences}&lt;/value&gt;
+&lt;extension&gt;
+${Dimont_ps_Input_sequences.ext}&lt;/extension&gt;
+&lt;/Dimont_ps_Input_sequences&gt;
+
+&lt;Dimont_ps_Position_tag&gt;
+${Dimont_ps_Position_tag}&lt;/Dimont_ps_Position_tag&gt;
+
+&lt;Dimont_ps_Value_tag&gt;
+${Dimont_ps_Value_tag}&lt;/Dimont_ps_Value_tag&gt;
+
+&lt;Dimont_ps_Standard_deviation&gt;
+${Dimont_ps_Standard_deviation}&lt;/Dimont_ps_Standard_deviation&gt;
+
+&lt;Dimont_ps_Weighting_factor&gt;
+${Dimont_ps_Weighting_factor}&lt;/Dimont_ps_Weighting_factor&gt;
+
+&lt;Dimont_ps_Starts&gt;
+${Dimont_ps_Starts}&lt;/Dimont_ps_Starts&gt;
+
+&lt;Dimont_ps_Initial_motif_width&gt;
+${Dimont_ps_Initial_motif_width}&lt;/Dimont_ps_Initial_motif_width&gt;
+
+&lt;Dimont_ps_Markov_order_of_motif_model&gt;
+${Dimont_ps_Markov_order_of_motif_model}&lt;/Dimont_ps_Markov_order_of_motif_model&gt;
+
+&lt;Dimont_ps_Markov_order_of_background_model&gt;
+${Dimont_ps_Markov_order_of_background_model}&lt;/Dimont_ps_Markov_order_of_background_model&gt;
+
+&lt;Dimont_ps_Equivalent_sample_size&gt;
+${Dimont_ps_Equivalent_sample_size}&lt;/Dimont_ps_Equivalent_sample_size&gt;
+
+&lt;Dimont_ps_Delete_BSs_from_profile&gt;
+${Dimont_ps_Delete_BSs_from_profile}&lt;/Dimont_ps_Delete_BSs_from_profile&gt;
+
+</configfile>
+</configfiles>
+<outputs>
+<data format="html" name="summary" label="#if str($Dimont_jobname) == '' then $tool.name + ' on ' + $on_string else $Dimont_jobname#">
+</data>
+</outputs>
+<help>
+**Dimont** is a universal tool for de-novo motif discovery. Dimont has successfully been applied to ChIP-seq, ChIP-exo and protein-binding microarray (PBM) data.
+
+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.
+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. In addition, you need to provide an anchor position within the sequence. 
+In case of ChIP data, this anchor position could for instance be the peak summit.
+For instance, an annotated FastA file for ChIP-exo data comprising sequences of length 100 centered around the peak summit could look like::
+	
+	> peak: 50; signal: 515
+	ggccatgtgtatttttttaaatttccac...
+	> peak: 50; signal: 199
+	GGTCCCCTGGGAGGATGGGGACGTGCTG...
+	...
+
+where the anchor point is given as 50 for the first two sequences, and the confidence 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 and a Perl script_ for preparing data in the format required by Dimont.
+
+Accordingly, you would need to set the parameter "Position tag" to ``peak`` and the parameter "Value tag" to ``signal`` for the input file.
+
+For the standard deviation of the position prior, the initial motif length and the number of pre-optimization runs, we provide default values that worked well in our studies on ChIP and PBM data. 
+However, you may want adjust these parameters to meet your prior information.
+
+The parameter "Markov order of the motif model" sets the order of the inhomogeneous Markov model used for modeling the motif. If this parameter is set to ``0``, you obtain a position weight matrix (PWM) model. 
+If it is set to ``1``, you obtain a weight array matrix (WAM) model. You can set the order of the motif model to at most ``3``.
+
+The parameter "Markov order of the background model" sets the order of the homogeneous Markov model used for modeling positions not covered by a motif. 
+If this parameter is set to ``-1``, you obtain a uniform distribution, which worked well for ChIP data. For PBM data, orders of up to ``4`` resulted in an increased prediction performance in our case studies. The maximum allowed value is ``5``.
+
+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 "Equivalent sample size" reflects the strength of the influence of the prior on the model parameters, where higher values smooth out the parameters to a greater extent.
+
+The parameter "Delete BSs from profile" defines if BSs of already discovered motifs should be deleted, i.e., "blanked out", from the sequence before searching for futher motifs.
+
+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 Dimont.
+
+If you experience problems using Dimont, please contact_ us.
+
+.. _example: http://www.jstacs.de/downloads/dimont-example.fa
+.. _script: http://www.jstacs.de/index.php/Dimont#Data_preparation
+.. _Dimont: http://jstacs.de/index.php/Dimont
+.. _contact: mailto:grau@informatik.uni-halle.de
+</help>
+</tool>
+