Regional Admixture Mapping and Structured Association Testing: Conceptual Unification Using a General Linear Model

• Activity Number: 427
• Type: Contributed
• Date/Time: Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): David Redden*+ and Jasmin Divers and Kelly Vaughan and Hemant Tiwari and Mark Beasley and Jose R. Fernandez and Robert Kimberly and Rui Feng and Miguel Padilla and Nianjun Liu and Michael Miller and David B. Allison
• Companies: The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and The University of Alabama at Birmingham and University of Minnesota and The University of Alabama at Birmingham
• Keywords: errors in variables ; linear model ; admixture ; association studies

Abstract

Regional admixture mapping (RAM) uses individual genetic admixture estimates in order to identify genomic regions that may contain loci that influence phenotypes. Estimates of individual ancestry can be used in structured association tests (SAT) to reduce confounding due to population substructure. We provide a conceptual framework in which both RAM and SAT are special cases of a general linear model which allows for greater modeling flexibility, adaptation to multiple designs, inclusion of covariates and interaction terms, and multi-locus models. We clarify which variables are sufficient to condition upon in order to prevent spurious associations. This approach allows a far wider use of RAM and SAT models, using standard software, to address admixture as either a confounder of association studies or a tool for finding loci influencing complex phenotypes in diverse species.