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Bioinformatics Advance Access published online on December 9, 2008

Bioinformatics, doi:10.1093/bioinformatics/btn627
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

PASTAA: identifying transcription factors associated with sets of co-regulated genes

Helge G. Roider *, Thomas Manke , Sean O'Keeffe , Martin Vingron and Stefan A. Haas

Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin.

*To whom correspondence should be addressed. Dr. Helge Roider, E-mail: roider{at}molgen.mpg.de


   Abstract

Motivation: A major challenge in regulatory genomics is the identification of associations between functional categories of genes (e.g. tissues, metabolic pathways) and their regulating transcription factors. While, for a limited number of categories, the regulating transcription factors are already known, still for many functional categories the responsible factors remain to be elucidated.

Results: We put forward a novel method (PASTAA) for detecting transcriptions factors associated with functional categories, which utilises the prediction of binding affinities of a transcription factor to promoters. This binding strength information is compared to the likelihood of membership of the corresponding genes in the functional category under study. Coherence between the two ranked data sets is seen as an indicator of association between a transcription factor and the category. PASTAA is applied primarily to the determination of transcription factors driving tissue specific expression. We show that PASTAA is capable of recovering many transcription factors acting tissue specifically and, in addition, provides novel associations so far not detected by alternative methods. The application of PASTAA to detect transcription factors involved in the regulation of tissue specific gene expression revealed a remarkable number of experimentally supported associations. The validated success for various data sets implies that PASTAA can directly be applied for the detection of transcription factors associated with newly derived gene sets.

Availability: The PASTAA source code as well as a corresponding web interface is freely available at http://trap.molgen.mpg.de.

Contact: vingron{at}molgen.mpg.de

Associate Editor: Prof. Alfonso Valencia


Received on September 8, 2008; revised on November 13, 2008; accepted on December 1, 2008

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