A Locally Convoluted Cluster Model for Nucleosome Positioning Signals in Chemical Maps

Liqun Xi, Kristin Brogaard, Qingyang Zhang, Bruce Lindsay, Jonathan Widom, Jiping Wang*

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

The nucleosome is the fundamental packing unit of DNA in eukaryotic cells, and its positioning plays a critical role in regulation of gene expression and chromosome functions. Using a recently developed chemical mapping method, nucleosomes can be potentially mapped with an unprecedented single-base-pair resolution. Existence of overlapping nucleosomes due to cell mixture or cell dynamics, however, causes convolution of nucleosome positioning signals. In this article, we introduce a locally convoluted cluster model and a maximum likelihood deconvolution approach, and illustrate the effectiveness of this approach in quantification of the nucleosome positional signal in the chemical mapping data. Supplementary materials for this article are available online.

Original languageEnglish (US)
Pages (from-to)48-62
Number of pages15
JournalJournal of the American Statistical Association
Volume109
Issue number505
DOIs
StatePublished - Jan 1 2014

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Keywords

  • Chemical mapping
  • Deconvolution
  • EM algorithm
  • Negative binomial cluster model
  • Poisson cluster model

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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