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Detects differential binding in a quantitatively principled way by formally testing hypothesis of non-differential binding at each putative binding site. DBChIP assigns uncertainty measure (P-values) to each finding, and thus, proper error rate control can be achieved. Furthermore, when there are more than two conditions for comparison (K>2), DBChIP can be used to detect pairwise differences after the detection of overall differential binding. Moreover, DBChIP does not rely on a specific sequencing platform and can accommodate data from Illumina, SOLiD and other platforms.

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DBChIP classification

DBChIP specifications

Software type:
Restrictions to use:
Programming languages:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:

DBChIP distribution


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DBChIP support



  • Kun Liang <>


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Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA

Funding source(s)

National Institutes of Health grant HG003747, Department of Energy grant FG02-04ER25627

Link to literature

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