alexa Considerations to Calculate Expected Genotypic Frequencies and Formal Statistical Testing of Hardy-Weinberg Assumptions for nonpseudoautosomal X chromosome SNPs | Abstract
ISSN: 2157-7412

Journal of Genetic Syndromes & Gene Therapy
Open Access

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Considerations to Calculate Expected Genotypic Frequencies and Formal Statistical Testing of Hardy-Weinberg Assumptions for nonpseudoautosomal X chromosome SNPs

Fernando Pires Hartwig*

Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil

*Corresponding Author:
Fernando Pires Hartwig
Postgraduate Program in Epidemiology
Federal University of Pelotas, Pelotas, RS, Brazil
Tel: (5553) 81347172
Email: fernandophart[email protected]

Received date: April 17, 2014; Accepted date:July 28, 2014; Published date: July 31, 2014

Citation: Hartwig FP (2014) Considerations to Calculate Expected Genotypic Frequencies and Formal Statistical Testing of Hardy-Weinberg Assumptions for non-pseudoautosomal X chromosome SNPs. J Genet Syndr Gene Ther 4:231. doi: 10.4172/2157-7412.1000231

Copyright: © Hartwig FP. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

HWE is a popular concept from population genetics that provides the investigator with an expectation regarding how genotypes are distributed in a given population. Although relying on a set of assumptions, HWE has been proven useful for genetic studies and, among its several applications, has been used as a quality control metric in GWAS. In this correspondence, the calculation to obtain expected genotypic frequencies of non-pseudoautosomal X chromosome SNPs (assuming HWE holds) by weighting within-sex expected genotypic frequencies by the prevalence of the respective sex in the sample is shown. It is also described that, under the assumption that each sex represents 50% of the sample, a one degree of freedom test can be derived. The calculation is simple and intuitive and, therefore, straightforward to incorporate in routine quality control analyses. This correspondence fills an existing gap in GWAS and may contribute to future investigations.

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