A tiered hidden Markov model characterizes multi-scale chromatin states.
Genomics
; 102(1): 1-7, 2013 Jul.
Article
in En
| MEDLINE
| ID: mdl-23570996
ABSTRACT
Precise characterization of chromatin states is an important but difficult task for understanding the regulatory role of chromatin. A number of computational methods have been developed with varying levels of success. However, a remaining challenge is to model epigenomic patterns over multi-scales, as each histone mark is distributed with its own characteristic length scale. We developed a tiered hidden Markov model and applied it to analyze a ChIP-seq dataset in human embryonic stem cells. We identified a two-tier structure containing 15 distinct bin-level chromatin states grouped into three domain-level states. Whereas the bin-level states capture the local variation of histone marks, the domain-level states detect large-scale variations. Compared to bin-level states, the domain-level states are more robust and coherent. We also found active regions in intergenic regions that upon closer examination were expressed non-coding RNAs and pseudogenes. These results provide insights into an additional layer of complexity in chromatin organization.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Chromatin
/
Computational Biology
/
RNA, Untranslated
/
Embryonic Stem Cells
Type of study:
Health_economic_evaluation
/
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Genomics
Journal subject:
GENETICA
Year:
2013
Document type:
Article
Affiliation country:
United States