A powerful association test of multiple genetic variants using a random-effects model

• Published in: Statistics in medicine Vol. 33; no. 11; pp. 1816 - 1827
• Main Authors: Cheng, K.F., Lee, J.Y., Zheng, W., Li, C.
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 20.05.2014; Wiley Subscription Services, Inc
• Subjects: association test; Biological variation; Breast cancer; Breast Neoplasms - genetics; China; Computer Simulation; Female; Genetic Association Studies - methods; Genetic Predisposition to Disease; Genetic Variation - genetics; Genotype; Genotype & phenotype; Humans; Medical statistics; Models, Genetic; random-effects model; rare variant; Receptor, Fibroblast Growth Factor, Type 2 - genetics; Sample Size; sequencing-based study; Simulation; China; sequencing-based study; association test; rare variant; random-effects model

There is an emerging interest in sequencing‐based association studies of multiple rare variants. Most association tests suggested in the literature involve collapsing rare variants with or without weighting. Recently, a variance‐component score test [sequence kernel association test (SKAT)] was prop...