Content area

Abstract

ChromHMM outputs both the learned chromatin-state model parameters and the chromatin-state assignments for each genomic position. The learned emission and transition parameters are returned in both text and image format (Fig. 1), automatically grouping chromatin states with similar emission parameters or proximal genomic locations, although a user-specified reordering can also be used (Supplementary Figs. 12 and Supplementary Note). ChromHMM enables the study of the likely biological roles of each chromatin state based on enrichment in diverse external annotations and experimental data, shown as heat maps and tables (Fig. 1), both for direct genomic overlap and at various distances from a chromatin state.

Details

Title
ChromHMM: automating chromatin-state discovery and characterization
Author
Ernst, Jason; Kellis, Manolis
Pages
215-216
Publication year
2012
Publication date
Mar 2012
Publisher
Nature Publishing Group
ISSN
15487091
e-ISSN
15487105
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1038942450
Copyright
Copyright Nature Publishing Group Mar 2012