A wavelet approach to detect enriched regions and explore epigenomic landscapes

Nha H. Nguyen, An Vo, Kyoung Jae Won

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Epigenetic landscapes represent how cells regulate gene activity. To understand their effect on gene regulation, it is important to detect their occupancy in the genome. Unlike transcription factors whose binding regions are limited to narrow regions, histone modification marks are enriched over broader areas. The stochastic characteristics unique to each mark make it hard to detect their enrichment. Classically, a predefined window has been used to detect their enrichment. However, these approaches heavily rely on the predetermined parameters. Also, the window-based approaches cannot handle the enrichment of multiple marks. We propose a novel algorithm, called SeqW, to detect enrichment of multiple histone modification marks. SeqW applies a zooming approach to detect a broadly enriched domain. The zooming approach helps domain detection by increasing signal-to-noise ratio. The borders of the domains are detected by studying the characteristics of signals in the wavelet domain. We show that SeqW outperformed previous predictors in detecting broad peaks. Also, we applied SeqW in studying spatial combinations of histone modification patterns.

Original languageEnglish (US)
Pages (from-to)846-854
Number of pages9
JournalJournal of computational biology : a journal of computational molecular cell biology
Volume21
Issue number11
DOIs
StatePublished - Nov 1 2014
Externally publishedYes

Fingerprint

Histone Code
Epigenomics
Wavelets
Genes
Transcription factors
Gene expression
Signal to noise ratio
Gene Regulation
Transcription Factor
Signal-To-Noise Ratio
Predictors
Genome
Gene
Transcription Factors
Cell

Keywords

  • enriched region
  • histone modification
  • wavelet
  • zero-crossing

ASJC Scopus subject areas

  • Medicine(all)

Cite this

A wavelet approach to detect enriched regions and explore epigenomic landscapes. / Nguyen, Nha H.; Vo, An; Won, Kyoung Jae.

In: Journal of computational biology : a journal of computational molecular cell biology, Vol. 21, No. 11, 01.11.2014, p. 846-854.

Research output: Contribution to journalArticle

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