MotifAdjuster

by Jens Keilwagen, Jan Baumbach, Thomas A. Kohl and Ivo Grosse.

Description

Valuable binding site annotation data are stored in databases. However, several types of errors can, and do, occur in the process of manually incorporating annotation data from scientific literature into these databases. Here, we introduce MotifAdjuster, a software that helps to detect these errors, and we demonstrate its efficacy on public data sets.

Paper

The paper MotifAdjuster: a tool for computational reassessment of transcription factor binding site annotations has been published in Genome Biology.

Download

MotifAdjuster can be downloaded here.

Start instructions

If you have unzipped the archive, you can start the MotifAdjuster by invoking

java -cp ./:./jstacs-1.2.2.jar:./numericalMethods.jar MotifAdjuster <file> <ignoreChar> <length> <fgOrder> <fgEss> <bothStrands> <output> <sigma> <p(no motif)>

In Windows, you have to use ";" instead of ":" in the class path.

The arguments have the following meaning

name	comment	type
file	the location of the data set	String
ignoreChar	char for comment lines (e.g. for a FastA-file '>')	char
length	the motif length	int
fgOrder	the order of the inhomogeneous Markov model that is uses for the motif; 0 yields in a PWM	byte
ess	the equivalent sample size that is used for the mixture model	double >= 0
bothStrands	use both strands	boolean
output	output of the EM	boolean
sigma	the sigma of the truncated discrete Gaussian distribution	double>0
p(no motif)	the probability for finding no motif	0<=double<1

Remark

The authors of SeSiMCMC informed us that the performance of SeSiMCMC could be improved by using the latest version of SeSiMCMC (version 4.31 from 2009-04-23) and by using the advanced option Background model is common (static) set to the value TRUE. Hence, we provide an updated version of additional file 1.