Genomics Inform.  2018 Dec;16(4):e27. 10.5808/GI.2018.16.4.e27.

A Short Report on the Markov Property of DNA Sequences on 200-bp Genomic Units of Roadmap Genomics ChromHMM Annotations: A Computational Perspective

• Park HS

• KMID: 2439217
• DOI: http://doi.org/10.5808/GI.2018.16.4.e27

Abstract

The non-coding DNA in eukaryotic genomes encodes a language that programs chromatin accessibility, transcription factor binding, and various other activities. The objective of this study was to determine the effect of the primary DNA sequence on the epigenomic landscape across a 200-base pair of genomic units by integrating 127 publicly available ChromHMM BED files from the Roadmap Genomics project. Nucleotide frequency profiles of 127 chromatin annotations stratified by chromatin variability were analyzed and integrative hidden Markov models were built to detect Markov properties of chromatin regions. Our aim was to identify the relationship between DNA sequence units and their chromatin variability based on integrated ChromHMM datasets of different cell and tissue types.

Keyword

chromatin maps; computational epigenetics; Markov chain; noncoding DNA; nucleotide frequency patterns

MeSH Terms

Base Sequence*
Chromatin
Dataset
DNA*
Epigenomics
Genome
Genomics*
Markov Chains
Transcription Factors
Chromatin
DNA
Transcription Factors