ArticleGenomics2013
A tiered hidden Markov model characterizes multi-scale chromatin states.
Article in Genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- ChromGene: gene-based modeling of epigenomic data.Genome biology · 2023Article
- Integrative chromatin domain annotation through graph embedding of Hi-C data.Bioinformatics (Oxford, England) · 2023Article
- Continuous chromatin state feature annotation of the human epigenome.Bioinformatics (Oxford, England) · 2022Article
- Segmentation and genome annotation algorithms for identifying chromatin state and other genomic patterns.PLoS computational biology · 2021Review
- Applications of ENCODE data to Systematic Analyses via Data Integration.Current opinion in systems biology · 2018Article
- Chromatin-state discovery and genome annotation with ChromHMM.Nature protocols · 2017Review
- Choosing panels of genomics assays using submodular optimization.Genome biology · 2016Article
- hiHMM: Bayesian non-parametric joint inference of chromatin state maps.Bioinformatics (Oxford, England) · 2015Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.