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Exploring Diallelic Genetic Markers: The HardyWeinberg Package

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  • Graffelman, Jan

Abstract

Testing genetic markers for Hardy-Weinberg equilibrium is an important issue in genetic association studies. The HardyWeinberg package offers the classical tests for equilibrium, functions for power computation and for the simulation of marker data under equilibrium and disequilibrium. Functions for testing equilibrium in the presence of missing data by using multiple imputation are provided. The package also supplies various graphical tools such as ternary plots with acceptance regions, log-ratio plots and Q-Q plots for exploring the equilibrium status of a large set of diallelic markers. Classical tests for equilibrium and graphical representations for diallelic marker data are reviewed. Several data sets illustrate the use of the package.

Suggested Citation

  • Graffelman, Jan, 2015. "Exploring Diallelic Genetic Markers: The HardyWeinberg Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i03).
    • Handle: RePEc:jss:jstsof:v:064:i03
    DOI: http://hdl.handle.net/10.18637/jss.v064.i03
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    References listed on IDEAS

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    1. Jan Graffelman & Milagros Sánchez & Samantha Cook & Victor Moreno, 2013. "Statistical Inference for Hardy-Weinberg Proportions in the Presence of Missing Genotype Information," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-11, December.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Guido Consonni & Elias Moreno & Sergio Venturini, 2010. "Testing Hardy-Weinberg Equilibrium: an Objective Bayesian Analysis," Quaderni di Dipartimento 121, University of Pavia, Department of Economics and Quantitative Methods.
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    1. Jesyka Meléndez-Rosa & Ke Bi & Eileen A Lacey, 2018. "Genomic analysis of MHC-based mate choice in the monogamous California mouse," Behavioral Ecology, International Society for Behavioral Ecology, vol. 29(5), pages 1167-1180.
    2. Seong Kyu Han & Michelle T. McNulty & Christopher J. Benway & Pei Wen & Anya Greenberg & Ana C. Onuchic-Whitford & Dongkeun Jang & Jason Flannick & Noël P. Burtt & Parker C. Wilson & Benjamin D. Humph, 2023. "Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Juan Antonio Zarza-Rebollo & Esther Molina & Elena López-Isac & Ana M. Pérez-Gutiérrez & Blanca Gutiérrez & Jorge A. Cervilla & Margarita Rivera, 2022. "Interaction Effect between Physical Activity and the BDNF Val66Met Polymorphism on Depression in Women from the PISMA-ep Study," IJERPH, MDPI, vol. 19(4), pages 1-13, February.

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