HPeak: A HMM-based algorithm for defining read-enriched regions from massive parallel sequencing data

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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 at the University of Michigan, collaborated with Arul Chinnaiyan's lab at the University of Michigan.

 

Download


HPeak is currently an Open Source program. You may download it by clicking here.

 

Citation


HPeak has been submitted as an application note. Please cite 'http://www-personal.umich.edu/~qin/HPeak' at this moment.

 

Contact


Please contact us at qin@umich.edu if you have any comments, suggestions, or bug reports.

 

 

 


[ HPeak ] | Qin Lab | Chinnaiyan Lab ]