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A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data

Desmond S Lun1*, Ashley Sherrid23, Brian Weiner4, David R Sherman25 and James E Galagan46

Author Affiliations

1 Phenomics and Bioinformatics Research Centre, School of Mathematics and Statistics, and Australian Centre for Plant Functional Genomics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095, Australia

2 Seattle Biomedical Research Institute, 307 Westlake Avenue North, Suite 500, Seattle, WA 98109, USA

3 Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA 98195, USA

4 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA

5 Department of Global Health, University of Washington, Seattle, WA 98195, USA

6 Department of Biomedical Engineering and Department of Microbiology, Boston University, 44 Cummington Street, Boston, MA 02215, USA

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Genome Biology 2009, 10:R142  doi:10.1186/gb-2009-10-12-r142

Published: 22 December 2009

Abstract

We present CSDeconv, a computational method that determines locations of transcription factor binding from ChIP-seq data. CSDeconv differs from prior methods in that it uses a blind deconvolution approach that allows closely-spaced binding sites to be called accurately. We apply CSDeconv to novel ChIP-seq data for DosR binding in Mycobacterium tuberculosis and to existing data for GABP in humans and show that it can discriminate binding sites separated by as few as 40 bp.