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1 <tool id="DimontPredictor" name="DimontPredictor" version="0.1" force_history_refresh="true">
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2 <description>for predicting binding sites using a Dimont model</description>
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3 <command>java -Xms256M -Xmx2G -jar \$JAR_PATH/DimontPredictorWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path</command>
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4 <inputs>
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5 <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)">
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6 </param>
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7 <param type="data" format="xml" name="DimontPredictor_ps_Dimont" label="<hr />Dimont" help="The trained Dimont classifier, i.e. the "Dimont" output of a previous Dimont run." value="" optional="false">
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8 </param>
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9
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10 <param type="data" format="fasta" name="DimontPredictor_ps_Input_sequences" label="<hr />Input sequences" help="The input sequences for de-novo motif discovery (can be uploaded using "GetData" -> "Upload File"), annotated FastA format. The required format is described in the help section." value="" optional="false">
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11 </param>
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12
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13 <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">
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14 </param>
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15
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16 <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">
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17 </param>
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18
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19 <param type="float" name="DimontPredictor_ps_p_value" label="<hr />p-value" help="The maximum p-value allowed for predicted binding sites" value="0.0010" optional="false">
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20 <validator type="in_range" min="0.0" max="1.0" message="Value is not in the specified range [0.0, 1.0]."/></param>
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21
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22 </inputs>
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23 <requirements>
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24 <requirement type="set_environment">JAR_PATH</requirement>
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25 <requirement type="binary" version=">=1.6">java</requirement>
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26 </requirements>
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27 <configfiles>
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28 <configfile name="script_file">
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29 <DimontPredictor_ps_Dimont>
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30 <value>
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31 ${DimontPredictor_ps_Dimont}</value>
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32 <extension>
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33 ${DimontPredictor_ps_Dimont.ext}</extension>
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34 </DimontPredictor_ps_Dimont>
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35
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36 <DimontPredictor_ps_Input_sequences>
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37 <value>
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38 ${DimontPredictor_ps_Input_sequences}</value>
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39 <extension>
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40 ${DimontPredictor_ps_Input_sequences.ext}</extension>
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41 </DimontPredictor_ps_Input_sequences>
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42
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43 <DimontPredictor_ps_Value_tag>
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44 ${DimontPredictor_ps_Value_tag}</DimontPredictor_ps_Value_tag>
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45
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46 <DimontPredictor_ps_Weighting_factor>
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47 ${DimontPredictor_ps_Weighting_factor}</DimontPredictor_ps_Weighting_factor>
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48
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49 <DimontPredictor_ps_p_value>
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50 ${DimontPredictor_ps_p_value}</DimontPredictor_ps_p_value>
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51
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52 </configfile>
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53 </configfiles>
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54 <outputs>
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55 <data format="html" name="summary" label="#if str($DimontPredictor_jobname) == '' then $tool.name + ' on ' + $on_string else $DimontPredictor_jobname#">
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56 </data>
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57 </outputs>
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58 <tests>
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59 <test>
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60 <param name="DimontPredictor_jobname" value="Test" />
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61 <param name="DimontPredictor_ps_Dimont" value="predictor_test.xml" ftype="xml" />
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62 <param name="DimontPredictor_ps_Input_sequences" value="dimont_test.fasta" />
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63 <param name="DimontPredictor_ps_Value_tag" label="Value tag" value="maxT" />
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64 <param name="DimontPredictor_ps_Weighting_factor" value="0.2" />
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65 <param name="DimontPredictor_ps_p_value" value="0.0010" />
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66 <output name="summary" file="TestPred/TestPred_html.html" />
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67 </test>
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68 </tests>
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69 <help>
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70 **DimontPredictor** allows for predicting binding sites in new data using a previously trained Dimont model. For training a Dimont model see tool "Dimont".
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71
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72 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.
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73
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74 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.
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75 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.
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76 Such confidences may be peak statistics (e.g., number of fragments under a peak) for ChIP data or signal intensities for PBM data.
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77
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78 For instance, an annotated FastA file for ChIP-exo data could look like::
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79
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80 > signal: 515
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81 ggccatgtgtatttttttaaatttccac...
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82 > signal: 199
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83 GGTCCCCTGGGAGGATGGGGACGTGCTG...
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84 ...
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85
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86 where the confidence for the first two sequences amounts to 515 and 199, respectively.
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87 The FastA comment may contain additional annotations of the format ``key1 : value1; key2: value2;...``.
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88 We also provide an example_ input file.
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89
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90 Accordingly, you would need to set the parameter "Value tag" to ``signal`` for this input file.
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91
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92 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.
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93 For PBM data, containing a large number of unspecific probes, this parameter should be set to a lower value, e.g. ``0.01``.
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94
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95 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.
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96 The Dimont tool uses a p-value threshold of ``1E-3``, which is also the default value of DimontPredictor.
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97
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98 You can also install this web-application within your local Galaxy server. Instructions can be found at the Dimont_ page of Jstacs.
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99 There you can also download a command line version of DimontPredictor.
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100
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101 If you experience problems using DimontPredictor, please contact_ us.
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102
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103 .. _example: http://www.jstacs.de/downloads/dimont-example.fa
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104 .. _Dimont: http://jstacs.de/index.php/Dimont
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105 .. _contact: mailto:grau@informatik.uni-halle.de
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106 </help>
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107 </tool>
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108
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