PMMdeNovo: Difference between revisions

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=== BindingSitePrediction ===
=== BindingSitePrediction ===
The tool [http://www2.informatik.uni-halle.de/agbio/publications/PMMdenovo/BindingSitePrediction.jar BindingSitePrediction] predicts instances of binding sites in a positive data set based on a previously learned model.
The tool [http://www2.informatik.uni-halle.de/agbio/publications/PMMdenovo/BindingSitePrediction.jar BindingSitePrediction] predicts instances of binding sites in a positive data set based on a previously learned model.
Run by calling
<code>java -jar BindingSitePrediction.jar modelFile dataPos dataNeg alpha output</code>
where the arguments have the following semantics:
<table border=0 cellpadding=10 align="center">
<tr>
<td>name</td>
<td>type</td>
        <td>default</td>
<td>comment</td>
</tr>
<tr><td colspan=4><hr></td></tr>
<tr>
<td><font color="green">modelFile</font></td>
<td>String</td>
<td>--</td>
<td>The location of the .xml representation (output of ModelTrainer) of the learned model.</td>
</tr>
<tr>
<td><font color="green">dataPos</font></td>
<td>String</td>
<td>--</td>
<td>The location of the positive data (fasta file or plain text) in which binding site locations are to be identified.</td>
</tr>
<tr>
<td><font color="green">dataNeg</font></td>
<td>String</td>
<td>--</td>
<td>The location of the negative data (fasta file or plain text) that is used for computing the prediction threshold.</td>
</tr>
<tr>
<td><font color="green">alpha</font></td>
<td>Integer</td>
<td>1E-4</td>
<td>Significance level on negative data.</td>
</tr>
<tr>
<td><font color="green">output</font></td>
<td>String</td>
<td>bindingSites.txt</td>
<td>Location of output file for writing the predicted binding sites.</td>
</tr>
</table>


=== Classification ===
=== Classification ===

Revision as of 14:05, 21 February 2015

by Ralf Eggeling, Teemu Roos, Petri Myllymäki, and Ivo Grosse

Runnable JARs

The application consists of three independent tools.

ModelTrainer

The tool ModelTrainer performs a de novo motif discovery on a set of putative non aligned sequences. It infers an inhomogenous PMM of arbitrary order, where order 0 corresponds to a PWM model. Run by calling

java -jar InhPMM.jar inputFile motifWidth motifOrder flankingOrder initSteps addSteps restarts output

where the arguments have the following semantics:

name type default comment

inputFile String -- The location of a text file containing the input sequences. If the first character in the file is '>' the content is interpreted interpreted as fasta file. Otherwise it is interpreted as plain text, i.e., each line corresponding to one sequence.
motifWidth Integer 20 The width of the motif to be inferred.
motifOrder Integer 2 The initial order of the inhomogeneous PMM, i.e., the number of context positions that can be taken into account for modeling intra-motif dependencies.
flankingOrder Integer 2 The order of the homogenous Markov model, which is used for modeling the flanking sequences that do not belong to the motif.
initSteps Integer 50 The number of initial iterations steps that the algorithm is always run for each restart.
addSteps Integer 10 The number of additional iterations steps, i.e., the number of iterations that have to be performed after having obtained the last optimal model structure before termination is allowed.
restarts Integer 10 The number of restarts of the algorithm.
output String model The path and file prefix for the output files. The tool produces two files, namely (i) output.xml containing the learned model and (ii) output.dot containing the graphViz representation of the learned PCT structures.

BindingSitePrediction

The tool BindingSitePrediction predicts instances of binding sites in a positive data set based on a previously learned model. Run by calling

java -jar BindingSitePrediction.jar modelFile dataPos dataNeg alpha output

where the arguments have the following semantics:

name type default comment

modelFile String -- The location of the .xml representation (output of ModelTrainer) of the learned model.
dataPos String -- The location of the positive data (fasta file or plain text) in which binding site locations are to be identified.
dataNeg String -- The location of the negative data (fasta file or plain text) that is used for computing the prediction threshold.
alpha Integer 1E-4 Significance level on negative data.
output String bindingSites.txt Location of output file for writing the predicted binding sites.

Classification

The tool Classification performs first a motif discovery with subsequent fragment-based classification using positive data that is assumed to contain an instance of the motif, and negative data that is assumed not to contain the motif. The tool returns the classification results to the standard output.

Data

The exemplary data sets contain extracted ChIP seq sequences of 50 different human transcription factors from the ENCODE project, as well as corresponding negative data. All data sets are split into 10 different subsets for enabling a reproducible 10-fold cross validation.

Source code

Building the source code requires Jstacs 2.1.