title: A 2-step penalized regression method for family-based next-generation sequencing association studies.
abstract: Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.
authors.affiliation: Department of Biostatistics, University of Kentucky College of Public Health, 111 Washington Ave, Lexington, KY 40536-0003, USA.
authors.forename: Xiuhua
authors.initials: X
authors.lastname: Ding
authors.affiliation: Institute of Public and Preventive Health, Department of Pediatrics, Georgia Health Sciences University, School of Medicine, Georgia Prevention Center, HS-1640, Augusta, GA 30912, USA.
authors.forename: Shaoyong
authors.initials: S
authors.lastname: Su
authors.affiliation: Department of Biostatistics, University of Kentucky College of Public Health, 111 Washington Ave, Lexington, KY 40536-0003, USA.
authors.forename: Kannabiran
authors.initials: K
authors.lastname: Nandakumar
authors.affiliation: Institute of Public and Preventive Health, Department of Pediatrics, Georgia Health Sciences University, School of Medicine, Georgia Prevention Center, HS-1640, Augusta, GA 30912, USA.
authors.forename: Xiaoling
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Biostatistics, University of Kentucky College of Public Health, 111 Washington Ave, Lexington, KY 40536-0003, USA.
authors.forename: David W
authors.initials: DW
authors.lastname: Fardo