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Statistical methods for genome-wide association studies

Lookup NU author(s): Professor Heather Cordell

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Abstract

© 2018 Elsevier Ltd Genome-wide association studies (GWAS) detect common genetic variants associated with complex disorders. With their comprehensive coverage of common single nucleotide polymorphisms and comparatively low cost, GWAS are an attractive tool in the clinical and commercial genetic testing. This review introduces the pipeline of statistical methods used in GWAS analysis, from data quality control, association tests, population structure control, interaction effects and results visualization, through to post-GWAS validation methods and related issues.

Publication metadata

Author(s): Wang MH, Cordell HJ, Van Steen K

Publication type: Article

Publication status: Published

Journal: Seminars in Cancer Biology

Year: 2019

Volume: 55

Pages: 53-60

Print publication date: 01/04/2019

Online publication date: 01/05/2018

Acceptance date: 28/04/2018

ISSN (print): 1044-579X

ISSN (electronic): 1096-3650

Publisher: Academic Press

URL: https://doi.org/10.1016/j.semcancer.2018.04.008

DOI: 10.1016/j.semcancer.2018.04.008

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