A Tutorial of the Poisson Random Field Model in Population Genetics. (3rd June 2008)

• Record Type: Journal Article
• Authors: Sethupathy, Praveen; Hannenhalli, Sridhar
• Other Names: Zelikovsky Alexander Academic Editor.
• Is Part Of: Advances in bioinformatics. Volume 2008(2008)
• Publication Date: 2008-06-03
• Subjects: Bioinformatics -- Periodicals; Bioinformatics; Computational Biology -- Periodicals; Periodicals; 570.285
• DOI: 10.1155/2008/257864
• Languages: English
• ISSNs: 1687-8027

Abstract

Abstract : Population genetics is the study of allele frequency changes driven by various evolutionary forces such as mutation, natural selection, and random genetic drift. Although natural selection is widely recognized as a bona-fide phenomenon, the extent to which it drives evolution continues to remain unclear and controversial. Various qualitative techniques, or so-called "tests of neutrality", have been introduced to detect signatures of natural selection. A decade and a half ago, Stanley Sawyer and Daniel Hartl provided a mathematical framework, referred to as the Poisson random field (PRF), with which to determine quantitatively the intensity of selection on a particular gene or genomic region. The recent availability of large-scale genetic polymorphism data has sparked widespread interest in genome-wide investigations of natural selection. To that end, the original PRF model is of particular interest for geneticists and evolutionary genomicists. In this article, we will provide a tutorial of the mathematical derivation of the original Sawyer and Hartl PRF model.