Views on GWAS statistical analysis

Date

2020

Authors

Cao, X.
Xing, L.
He, H.
Zhang, Xuekui

Journal Title

Journal ISSN

Volume Title

Publisher

Bioinformation

Abstract

Genome-wide association study (GWAS) is a popular approach to investigate relationships between genetic information and diseases. A number of associations are tested in a study and the results are often corrected using multiple adjustment methods. It is observed that GWAS studies suffer adequate statistical power for reliability. Hence, we document known models for reliability assessment using improved statistical power in GWAS analysis.

Description

Keywords

genome-wide assocation studies, single nucleotide polymorphisms, statistical power, multiple testing adjustment, linkage disequilibrium, supervised learning, unsupervised learning

Citation

Cao, X., Xing, L., He, H., Zhang, X. (2020). Views on GWAS statistical analysis. Bioinformatics, 16(5). https://doi.org/10.6026/97320630016393