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Statistical Applications in Genetics and Molecular Biology

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Volume 14, Issue 6 (Dec 2015)

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Using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling

Rawane Samb
  • Centre de Recherche du CHU de Québec – Pavillon CHUL, Faculté de Médecine, Université Laval, 2705 Boulevard Laurier, Québec, QC G1V 4G2, Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Khader Khadraoui / Pascal Belleau
  • Centre de Recherche du CHU de Québec – Pavillon CHUL, Faculté de Médecine, Université Laval, 2705 Boulevard Laurier, Québec, QC G1V 4G2, Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Astrid Deschênes
  • Centre de Recherche du CHU de Québec – Pavillon CHUL, Faculté de Médecine, Université Laval, 2705 Boulevard Laurier, Québec, QC G1V 4G2, Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Lajmi Lakhal-Chaieb / Arnaud Droit
  • Corresponding author
  • Centre de Recherche du CHU de Québec – Pavillon CHUL, Faculté de Médecine, Université Laval, 2705 Boulevard Laurier, Québec, QC G1V 4G2, Canada
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Published Online: 2015-12-10 | DOI: https://doi.org/10.1515/sagmb-2014-0098

Abstract

Genome-wide mapping of nucleosomes has revealed a great deal about the relationships between chromatin structure and control of gene expression. Recent next generation CHIP-chip and CHIP-Seq technologies have accelerated our understanding of basic principles of chromatin organization. These technologies have taught us that nucleosomes play a crucial role in gene regulation by allowing physical access to transcription factors. Recent methods and experimental advancements allow the determination of nucleosome positions for a given genome area. However, most of these methods estimate the number of nucleosomes either by an EM algorithm using a BIC criterion or an effective heuristic strategy. Here, we introduce a Bayesian method for identifying nucleosome positions. The proposed model is based on a Multinomial-Dirichlet classification and a hierarchical mixture distributions. The number and the positions of nucleosomes are estimated using a reversible jump Markov chain Monte Carlo simulation technique. We compare the performance of our method on simulated data and MNase-Seq data from Saccharomyces cerevisiae against PING and NOrMAL methods.

This article offers supplementary material which is provided at the end of the article.

Keywords: Bayesian t-mixture; genome-wide profiling; Multinomial-Dirichlet prior; nucleosome positioning; reversible-jump MCMC

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About the article

Corresponding author: Arnaud Droit, Centre de Recherche du CHU de Québec – Pavillon CHUL, Faculté de Médecine, Université Laval, 2705 Boulevard Laurier, R-4773, Québec, QC G1V 4G2, Canada, e-mail:

aRawane Samb, Khader Khadraoui and Pascal Belleau: These authors contributed equally to this work.


Published Online: 2015-12-10

Published in Print: 2015-12-01


Citation Information: Statistical Applications in Genetics and Molecular Biology, ISSN (Online) 1544-6115, ISSN (Print) 2194-6302, DOI: https://doi.org/10.1515/sagmb-2014-0098.

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