Detecting DNA regulatory motifs by incorporating positional trends in information content
1 Department of Statistics, University of California, Berkeley, CA 94720, USA
2 Department of Genome Sciences, Life Sciences Division, Ernest Orlando Lawrence Berkeley National Lab, Cyclotron Road, Berkeley, CA 94720, USA
3 Center for Integrative Genomics, Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
4 Current address: Department of Biochemistry and Biophysics, 600 16th Street 2240, University of California, San Francisco, CA 94143, USA
5 Current address: Mathematical Institute, University Leiden, 2300 RA Leiden, The Netherlands
Genome Biology 2004, 5:R50 doi:10.1186/gb-2004-5-7-r50Published: 24 June 2004
On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods. We assign position-specific prior distributions to the frequency parameters of the model, penalizing deviations from a specified conservation profile. Examples with both simulated and real data show that this extension helps discover motifs as the data become noisier or when there is a competing false motif.