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1 <tool id="Dimont" name="Dimont" version="0.1" force_history_refresh="true">
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17
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2 <description>- a universal tool for de-novo motif discovery.</description>
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3 <command>java -Xms256M -Xmx2G -jar \$JAR_PATH/DimontWeb.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="Dimont_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="fasta" name="Dimont_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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8 </param>
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9
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10 <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">
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11 </param>
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12
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13 <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">
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14 </param>
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15
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16 <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">
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17 <validator type="in_range" min="1.0" max="10000.0" message="Value is not in the specified range [1.0, 10000.0]."/></param>
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18
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19 <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">
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20 </param>
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21
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22 <param type="integer" name="Dimont_ps_Starts" label="<hr />Starts" help="The number of pre-optimization runs." value="20" optional="false">
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23 <validator type="in_range" min="1" max="100" message="Value is not in the specified range [1, 100]."/></param>
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24
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25 <param type="integer" name="Dimont_ps_Initial_motif_width" label="<hr />Initial motif width" help="The motif width that is used initially, may be adjusted during optimization." value="15" optional="false">
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26 <validator type="in_range" min="1" max="50" message="Value is not in the specified range [1, 50]."/></param>
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27
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28 <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">
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29 <validator type="in_range" min="0" max="3" message="Value is not in the specified range [0, 3]."/></param>
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30
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31 <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">
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32 <validator type="in_range" min="-1" max="5" message="Value is not in the specified range [-1, 5]."/></param>
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33
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34 <param type="float" name="Dimont_ps_Equivalent_sample_size" label="<hr />Equivalent sample size" help="Reflects the strength of the prior on the model parameters." value="4.0" optional="false">
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35 <validator type="in_range" min="0.0" max="Infinity" message="Value is not in the specified range [0.0, Infinity]."/></param>
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36
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37 <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">
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38 </param>
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39
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40 </inputs>
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41 <requirements>
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42 <requirement type="set_environment">JAR_PATH</requirement>
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43 <requirement type="binary" version=">=1.6">java</requirement>
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44 </requirements>
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45 <configfiles>
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46 <configfile name="script_file">
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47 <Dimont_ps_Input_sequences>
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48 <value>
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49 ${Dimont_ps_Input_sequences}</value>
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50 <extension>
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51 ${Dimont_ps_Input_sequences.ext}</extension>
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52 </Dimont_ps_Input_sequences>
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53
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54 <Dimont_ps_Position_tag>
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55 ${Dimont_ps_Position_tag}</Dimont_ps_Position_tag>
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56
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57 <Dimont_ps_Value_tag>
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58 ${Dimont_ps_Value_tag}</Dimont_ps_Value_tag>
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59
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60 <Dimont_ps_Standard_deviation>
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61 ${Dimont_ps_Standard_deviation}</Dimont_ps_Standard_deviation>
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62
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63 <Dimont_ps_Weighting_factor>
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64 ${Dimont_ps_Weighting_factor}</Dimont_ps_Weighting_factor>
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65
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66 <Dimont_ps_Starts>
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67 ${Dimont_ps_Starts}</Dimont_ps_Starts>
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68
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69 <Dimont_ps_Initial_motif_width>
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70 ${Dimont_ps_Initial_motif_width}</Dimont_ps_Initial_motif_width>
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71
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72 <Dimont_ps_Markov_order_of_motif_model>
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73 ${Dimont_ps_Markov_order_of_motif_model}</Dimont_ps_Markov_order_of_motif_model>
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74
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75 <Dimont_ps_Markov_order_of_background_model>
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76 ${Dimont_ps_Markov_order_of_background_model}</Dimont_ps_Markov_order_of_background_model>
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77
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78 <Dimont_ps_Equivalent_sample_size>
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79 ${Dimont_ps_Equivalent_sample_size}</Dimont_ps_Equivalent_sample_size>
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80
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81 <Dimont_ps_Delete_BSs_from_profile>
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82 ${Dimont_ps_Delete_BSs_from_profile}</Dimont_ps_Delete_BSs_from_profile>
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83
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84 </configfile>
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85 </configfiles>
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86 <outputs>
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87 <data format="html" name="summary" label="#if str($Dimont_jobname) == '' then $tool.name + ' on ' + $on_string else $Dimont_jobname#">
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88 </data>
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89 </outputs>
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90 <tests>
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91 <test>
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92 <param name="Dimont_jobname" value="Test" />
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93 <param name="Dimont_ps_Input_sequences" value="dimont_test.fasta" />
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94 <param name="Dimont_ps_Position_tag" value="peakSummit" />
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95 <param name="Dimont_ps_Value_tag" value="maxT" />
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96 <param name="Dimont_ps_Standard_deviation" value="75.0" />
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97 <param name="Dimont_ps_Weighting_factor" value="0.2" />
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98 <param name="Dimont_ps_Starts" value="20" />
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99 <param name="Dimont_ps_Initial_motif_width" value="15" />
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100 <param name="Dimont_ps_Markov_order_of_motif_model" value="0" />
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101 <param name="Dimont_ps_Markov_order_of_background_model" value="-1" />
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102 <param name="Dimont_ps_Equivalent_sample_size" value="4.0" />
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103 <param name="Dimont_ps_Delete_BSs_from_profile" value="True" />
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104 <output name="summary" file="Test/Test_html.html" />
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105 </test>
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106 </tests>
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107 <help>
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108 **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.
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109
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110 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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111 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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112 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.
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113 In case of ChIP data, this anchor position could for instance be the peak summit.
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114 For instance, an annotated FastA file for ChIP-exo data comprising sequences of length 100 centered around the peak summit could look like::
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115
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116 > peak: 50; signal: 515
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117 ggccatgtgtatttttttaaatttccac...
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118 > peak: 50; signal: 199
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119 GGTCCCCTGGGAGGATGGGGACGTGCTG...
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120 ...
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121
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122 where the anchor point is given as 50 for the first two sequences, and the confidence amounts to 515 and 199, respectively.
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123 The FastA comment may contain additional annotations of the format ``key1 : value1; key2: value2;...``.
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124 We also provide an example_ input file and a Perl script_ for preparing data in the format required by Dimont.
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125
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126 Accordingly, you would need to set the parameter "Position tag" to ``peak`` and the parameter "Value tag" to ``signal`` for the input file.
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127
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128 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.
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129 However, you may want adjust these parameters to meet your prior information.
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130
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131 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.
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132 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``.
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133
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134 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.
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135 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``.
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136
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137 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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138 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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139
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140 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.
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141
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142 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.
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143
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144 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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145 There you can also download a command line version of Dimont.
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146
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147 If you experience problems using Dimont, please contact_ us.
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148
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149 .. _example: http://www.jstacs.de/downloads/dimont-example.fa
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150 .. _script: http://www.jstacs.de/index.php/Dimont#Data_preparation
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151 .. _Dimont: http://jstacs.de/index.php/Dimont
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152 .. _contact: mailto:grau@informatik.uni-halle.de
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153 </help>
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154 </tool>
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155
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