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Bioinformatics Advance Access published online on August 19, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth480
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received May 18, 2004
Revised July 28, 2004
Accepted August 13, 2004

Article

Similarity of position frequency matrices for transcription factor binding sites

Dustin E. Schones 1*, Pavel Sumazin 2, Michael Q. Zhang 3

1 Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA; Department of Physics and Astronomy, State University of New York, Stony Brook, NY 11794, USA
2 Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA; Computer Science Department, Portland State University, P.O. Box 751, Portland, OR 97207, USA
3 Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA

* To whom correspondence should be addressed. E-mail: dschones{at}cshl.edu.


  Abstract

Motivation: Transcription-factor binding sites in promoter sequences of higher eukaryotes are commonly modeled using position frequency matrices. The ability to compare position frequency matrices representing binding sites is especially important for de novo sequence motif discovery, where it is desirable to compare putative matrices to one another and to known matrices.

Results: We describe a position frequency matrix similarity quantification method based on product-multinomial distributions, demonstrate its ability to identify position frequency matrix similarity and show that it has a better false positive to false negative ratio compared to existing methods.

We group transcription factor binding site frequency matrices from two libraries into matrix families, and identify the matrices that are common and unique to these libraries. We identify similarities and differences between the skeletal-muscle-specific and non-muscle-specific frequency matrices for the binding sites of Mef-2, Myf, Sp-1, SRF and TEF of Wasserman and Fickett (1998). We further identify known frequency matrices and matrix families that are strongly similar to the matrices given by Wasserman and Fickett. We provide methodology and tools to compare and query libraries of frequency matrices for transcription factor binding sites.

Availability: Software is available to use over the web at http://rulai.cshl.edu/MatCompare.

Supplementary Information: Database and clustering statistics, matrix families, and representatives are available at http://rulai.cshl.edu/MatCompare/Supplementary.


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