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Bioinformatics. 2010 Dec 15;26(24):3028-34. doi: 10.1093/bioinformatics/btq590. Epub 2010 Oct 21.

Discovering homotypic binding events at high spatial resolution.

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  • 1MIT Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.



Clusters of protein-DNA interaction events involving the same transcription factor are known to act as key components of invertebrate and mammalian promoters and enhancers. However, detecting closely spaced homotypic events from ChIP-Seq data is challenging because random variation in the ChIP fragmentation process obscures event locations.


The Genome Positioning System (GPS) can predict protein-DNA interaction events at high spatial resolution from ChIP-Seq data, while retaining the ability to resolve closely spaced events that appear as a single cluster of reads. GPS models observed reads using a complexity penalized mixture model and efficiently predicts event locations with a segmented EM algorithm. An optional mode permits GPS to align common events across distinct experiments. GPS detects more joint events in synthetic and actual ChIP-Seq data and has superior spatial resolution when compared with other methods. In addition, the specificity and sensitivity of GPS are superior to or comparable with other methods.


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