An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research. (March 2018)

• Record Type: Journal Article
• Authors: Buu, Anne; Williams, L Keoki; Yang, James J
• Other Names: Nakas Christos T guest-editor.; Reiser Benjamin guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 27:Number 3(2018)
• Page Start: 905
• Page End: 919
• Publication Date: 2018-03
• Subjects: Genome-wide association study -- Fisher combination function -- multivariate permutation -- substance abuse; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280216647422
• Languages: English
• ISSNs: 0962-2802

Abstract

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher's combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.