# HG changeset patch
# User grau
# Date 1383756722 18000
# Node ID ecf3bb612a6a4acd0a950babc230488df32861d4
# Parent 93f3b1563fa6195d33f04bad96bbbe153ce236cd
Uploaded
diff -r 93f3b1563fa6 -r ecf3bb612a6a DimontWeb.jar
Binary file DimontWeb.jar has changed
diff -r 93f3b1563fa6 -r ecf3bb612a6a DimontWeb.xml
--- a/DimontWeb.xml Wed Nov 06 11:04:57 2013 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,134 +0,0 @@
-
-Dimont, a universal tool for de-novo motif discovery (beta).
-java -Xms256M -Xmx2G -jar /Users/dev/Desktop/ChIP-seq/galaxy/DimontWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path
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-<Dimont_ps_Input_sequences>
-<value>
-${Dimont_ps_Input_sequences}</value>
-<extension>
-${Dimont_ps_Input_sequences.ext}</extension>
-</Dimont_ps_Input_sequences>
-
-<Dimont_ps_Position_tag>
-${Dimont_ps_Position_tag}</Dimont_ps_Position_tag>
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-<Dimont_ps_Value_tag>
-${Dimont_ps_Value_tag}</Dimont_ps_Value_tag>
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-<Dimont_ps_Standard_deviation>
-${Dimont_ps_Standard_deviation}</Dimont_ps_Standard_deviation>
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-<Dimont_ps_Weighting_factor>
-${Dimont_ps_Weighting_factor}</Dimont_ps_Weighting_factor>
-
-<Dimont_ps_Starts>
-${Dimont_ps_Starts}</Dimont_ps_Starts>
-
-<Dimont_ps_Initial_motif_width>
-${Dimont_ps_Initial_motif_width}</Dimont_ps_Initial_motif_width>
-
-<Dimont_ps_Markov_order_of_motif_model>
-${Dimont_ps_Markov_order_of_motif_model}</Dimont_ps_Markov_order_of_motif_model>
-
-<Dimont_ps_Markov_order_of_background_model>
-${Dimont_ps_Markov_order_of_background_model}</Dimont_ps_Markov_order_of_background_model>
-
-<Dimont_ps_Equivalent_sample_size>
-${Dimont_ps_Equivalent_sample_size}</Dimont_ps_Equivalent_sample_size>
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-<Dimont_ps_Delete_BSs_from_profile>
-${Dimont_ps_Delete_BSs_from_profile}</Dimont_ps_Delete_BSs_from_profile>
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-**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
-
-
-
diff -r 93f3b1563fa6 -r ecf3bb612a6a galaxy/._DimontWeb.jar
Binary file galaxy/._DimontWeb.jar has changed
diff -r 93f3b1563fa6 -r ecf3bb612a6a galaxy/DimontWeb.jar
Binary file galaxy/DimontWeb.jar has changed
diff -r 93f3b1563fa6 -r ecf3bb612a6a galaxy/DimontWeb.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/galaxy/DimontWeb.xml Wed Nov 06 11:52:02 2013 -0500
@@ -0,0 +1,137 @@
+
+Dimont, a universal tool for de-novo motif discovery (beta).
+java -Xms256M -Xmx2G -jar \$JAR_PATH/DimontWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path
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+ JAR_PATH
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+<Dimont_ps_Input_sequences>
+<value>
+${Dimont_ps_Input_sequences}</value>
+<extension>
+${Dimont_ps_Input_sequences.ext}</extension>
+</Dimont_ps_Input_sequences>
+
+<Dimont_ps_Position_tag>
+${Dimont_ps_Position_tag}</Dimont_ps_Position_tag>
+
+<Dimont_ps_Value_tag>
+${Dimont_ps_Value_tag}</Dimont_ps_Value_tag>
+
+<Dimont_ps_Standard_deviation>
+${Dimont_ps_Standard_deviation}</Dimont_ps_Standard_deviation>
+
+<Dimont_ps_Weighting_factor>
+${Dimont_ps_Weighting_factor}</Dimont_ps_Weighting_factor>
+
+<Dimont_ps_Starts>
+${Dimont_ps_Starts}</Dimont_ps_Starts>
+
+<Dimont_ps_Initial_motif_width>
+${Dimont_ps_Initial_motif_width}</Dimont_ps_Initial_motif_width>
+
+<Dimont_ps_Markov_order_of_motif_model>
+${Dimont_ps_Markov_order_of_motif_model}</Dimont_ps_Markov_order_of_motif_model>
+
+<Dimont_ps_Markov_order_of_background_model>
+${Dimont_ps_Markov_order_of_background_model}</Dimont_ps_Markov_order_of_background_model>
+
+<Dimont_ps_Equivalent_sample_size>
+${Dimont_ps_Equivalent_sample_size}</Dimont_ps_Equivalent_sample_size>
+
+<Dimont_ps_Delete_BSs_from_profile>
+${Dimont_ps_Delete_BSs_from_profile}</Dimont_ps_Delete_BSs_from_profile>
+
+
+
+
+
+
+
+
+**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
+
+
+
diff -r 93f3b1563fa6 -r ecf3bb612a6a galaxy/tool_dependencies.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/galaxy/tool_dependencies.xml Wed Nov 06 11:52:02 2013 -0500
@@ -0,0 +1,6 @@
+
+
+
+ $REPOSITORY_INSTALL_DIR
+
+
\ No newline at end of file