Shaun Purcell1, Pak Sham. 1. Whitehead Institute, Nine Cambridge Center, Cambridge, MA 02129, USA. soyrcekk@pngu.mgh.harvard.edu
Abstract
OBJECTIVE: To examine the properties of the structured association approach for the detection and correction of population stratification. METHOD: A method is developed, within a latent class analysis framework, similar to the methods proposed by Satten et al. (2001) and Pritchard et al. (2000). A series of simulations illustrate the relative impact of number and type of loci, sample size and population structure. RESULTS: The ability to detect stratification and assign individuals to population strata is determined for a number of different scenarios. CONCLUSION: The results underline the importance of careful marker selection.
OBJECTIVE: To examine the properties of the structured association approach for the detection and correction of population stratification. METHOD: A method is developed, within a latent class analysis framework, similar to the methods proposed by Satten et al. (2001) and Pritchard et al. (2000). A series of simulations illustrate the relative impact of number and type of loci, sample size and population structure. RESULTS: The ability to detect stratification and assign individuals to population strata is determined for a number of different scenarios. CONCLUSION: The results underline the importance of careful marker selection.
Authors: Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham Journal: Am J Hum Genet Date: 2007-07-25 Impact factor: 11.025
Authors: Melinda C Aldrich; Steve Selvin; Helen M Hansen; Lisa F Barcellos; Margaret R Wrensch; Jennette D Sison; Charles P Quesenberry; Rick A Kittles; Gabriel Silva; Patricia A Buffler; Michael F Seldin; John K Wiencke Journal: Am J Epidemiol Date: 2008-09-12 Impact factor: 4.897