Cao, X.Xing, L.He, H.Zhang, Xuekui2021-08-182021-08-1820202020Cao, X., Xing, L., He, H., Zhang, X. (2020). Views on GWAS statistical analysis. Bioinformatics, 16(5). https://doi.org/10.6026/97320630016393https://doi.org/10.6026/97320630016393http://hdl.handle.net/1828/13273Genome-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.engenome-wide assocation studiessingle nucleotide polymorphismsstatistical powermultiple testing adjustmentlinkage disequilibriumsupervised learningunsupervised learningArticleDepartment of Mathematics and Statistics