<![CDATA[BOL: ChromHMM: Chromatin state discovery and characterization]]> https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization? https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization Wed, 19 Apr 2017 04:06:23 -0500 https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization <![CDATA[ChromHMM: Chromatin state discovery and characterization]]> ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks. ChromHMM is based on a multivariate Hidden Markov Model that explicitly models the presence or absence of each chromatin mark. The resulting model can then be used to systematically annotate a genome in one or more cell types. By automatically computing state enrichments for large-scale functional and annotation datasets ChromHMM facilitates the biological characterization of each state. ChromHMM also produces files with genome-wide maps of chromatin state annotations that can be directly visualized in a genome browser. 

Address of the bookmark: http://compbio.mit.edu/ChromHMM/

]]> Abhimanyu Singh