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A Note on Exact Differences between Beta Distributions in Genomic (Methylation) Studies

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  • Emanuele Raineri
  • Marc Dabad
  • Simon Heath

Abstract

We apply a known algorithm for computing exactly inequalities between Beta distributions to assess whether a given position in a genome is differentially methylated across samples. We discuss the advantages brought by the adoption of this solution with respect to two approximations (Fisher's test and Z score). The same formalism presented here can be applied in a similar way to variant calling.

Suggested Citation

  • Emanuele Raineri & Marc Dabad & Simon Heath, 2014. "A Note on Exact Differences between Beta Distributions in Genomic (Methylation) Studies," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-5, May.
    • Handle: RePEc:plo:pone00:0097349
    DOI: 10.1371/journal.pone.0097349
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    1. Ryan Lister & Mattia Pelizzola & Robert H. Dowen & R. David Hawkins & Gary Hon & Julian Tonti-Filippini & Joseph R. Nery & Leonard Lee & Zhen Ye & Que-Minh Ngo & Lee Edsall & Jessica Antosiewicz-Bourg, 2009. "Human DNA methylomes at base resolution show widespread epigenomic differences," Nature, Nature, vol. 462(7271), pages 315-322, November.
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    Cited by:

    1. Greg Jensen & Fabian Muñoz & Yelda Alkan & Vincent P Ferrera & Herbert S Terrace, 2015. "Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model," PLOS Computational Biology, Public Library of Science, vol. 11(9), pages 1-27, September.

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