HPeak v2.1 is now available, and you may download the new version here.
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Overview
ChIP-Seq is an important application of the massively parallel sequencing technologies aiming to identify all the locations in the genome where a specific protein binds. While direct counting of the sequencing reads can reveal many such binding sites, it is desirable to develop a statistical sound method to explicitly model the uncertainties involved for better and more interpretable results. Here we present HPeak, a hidden Markov model-based approach that can accurately pinpoint regions to where significantly more sequence reads map. Testing on real data shows that these regions are indeed highly enriched by the right protein binding sites.
Authors
HPeak was developed by Steve Qin, Jincheng Shen, collaborated with Arul Chinnaiyan's lab at the University of Michigan.
Download
HPeak(v1.0) is currently an Open Source program. You may download it by clicking here.
HPeak v1.1 is currently available. You may download it by clicking here.
HPeak v2.1 is now available, and you may download the new version here.
Citation
To reference HPeak, please cite: Qin ZS, Yu J, Shen J, Maher CA, Hu M, Kalyana-Sundaram S, Yu J, Chinnaiyan AM (2010). HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data. BMC Bioinformatics, 11:369. (PDF)
Acknowledgement
We thank Dr. Chris Maher, Shanker Kalyana-Sundaram, Terrence Barrette and members of the Arul Chinaniyan Lab for valuable suggestions and comments on earlier versions of this program.
We thank BCGSC and Illumina for posting their data for downlaod.
We thank Dr. Hans-Jörg Warnatz of the Max Planck Institute for Molecular Genetics for valuable suggestions.
Contact
Comments, suggestions, questions are welcomed, and should be directed to Steve Qin. Email: qin@umich.edu. Phone: 734-763-5965
[ HPeak ] | Qin Lab | Chinnaiyan Lab ]