HMRFBayesHiC: A Hidden Markov Random Field Based Bayesian Method For the Detection of Long-range Chromosomal Interactions in Hi-C Data

HMRFBayesHiC is a hidden Markov random field based Bayesian peak caller to identify long range chromatin interactions from Hi-C data. Comparing to the existing anchor-fragment peak caller, HMRFBayesHiC is the first two-dimensional peak caller, which takes observed and expected Hi-C contact matrix as the input files. HMRFBayesHiC explicitly models the spatial dependency of chromatin interaction among adjacent neighborhood regions, resulting in superior reproducibility and enhanced statistical power. The current version is a pre-release. For details, please refer to our tutorial.

Comments and suggestions are welcome, please e-mail Zheng Xu at xuzheng@email.unc.edu or Ming Hu at hum@ccf.org or Yun Li at yunli@med.unc.edu.