Bayesian hidden Markov models to identify RNA-protein interaction sites in PAR-CLIP.

ABSTRACT: The photoactivatable ribonucleoside enhanced cross-linking immunoprecipitation (PAR-CLIP) has been increasingly used for the global mapping of RNA-protein interaction sites. There are two key features of the PAR-CLIP experiments: The sequence read tags are likely to form an enriched peak around each RNA-protein interaction site; and the cross-linking procedure is likely to introduce a specific mutation in each sequence read tag at the interaction site. Several ad hoc methods have been developed to identify the RNA-protein interaction sites using either sequence read counts or mutation counts alone; however, rigorous statistical methods for analyzing PAR-CLIP are still lacking. In this article, we propose an integrative model to establish a joint distribution of observed read and mutation c

SUBMITTER: Yun J 

PROVIDER: S-EPMC4061157 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature