Literature DB >> 25072902

A wavelet approach to detect enriched regions and explore epigenomic landscapes.

Nha Nguyen1, An Vo, Kyoung-Jae Won.   

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.

Keywords:  enriched region; histone modification; wavelet; zero-crossing

Mesh:

Substances:

Year:  2014        PMID: 25072902      PMCID: PMC4224055          DOI: 10.1089/cmb.2014.0095

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  27 in total

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2.  Unsupervised segmentation of continuous genomic data.

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Journal:  Bioinformatics       Date:  2007-03-23       Impact factor: 6.937

3.  A chromatin landmark and transcription initiation at most promoters in human cells.

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Journal:  Cell       Date:  2007-07-13       Impact factor: 41.582

4.  A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.

Authors:  Chongzhi Zang; Dustin E Schones; Chen Zeng; Kairong Cui; Keji Zhao; Weiqun Peng
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

5.  A wavelet-based method to exploit epigenomic language in the regulatory region.

Authors:  Nha Nguyen; An Vo; Kyoung-Jae Won
Journal:  Bioinformatics       Date:  2013-10-04       Impact factor: 6.937

6.  Histone modification levels are predictive for gene expression.

Authors:  Rosa Karlić; Ho-Ryun Chung; Julia Lasserre; Kristian Vlahovicek; Martin Vingron
Journal:  Proc Natl Acad Sci U S A       Date:  2010-02-01       Impact factor: 11.205

7.  Integrating multiple evidence sources to predict transcription factor binding in the human genome.

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8.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.

Authors:  Sven Heinz; Christopher Benner; Nathanael Spann; Eric Bertolino; Yin C Lin; Peter Laslo; Jason X Cheng; Cornelis Murre; Harinder Singh; Christopher K Glass
Journal:  Mol Cell       Date:  2010-05-28       Impact factor: 17.970

9.  Genome-wide prediction of transcription factor binding sites using an integrated model.

Authors:  Kyoung-Jae Won; Bing Ren; Wei Wang
Journal:  Genome Biol       Date:  2010-01-22       Impact factor: 13.583

10.  Identifying positioned nucleosomes with epigenetic marks in human from ChIP-Seq.

Authors:  Yong Zhang; Hyunjin Shin; Jun S Song; Ying Lei; X Shirley Liu
Journal:  BMC Genomics       Date:  2008-11-13       Impact factor: 3.969

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  1 in total

1.  A stationary wavelet entropy-based clustering approach accurately predicts gene expression.

Authors:  Nha Nguyen; An Vo; Inchan Choi; Kyoung-Jae Won
Journal:  J Comput Biol       Date:  2014-11-10       Impact factor: 1.479

  1 in total

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