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