Premium
Evaluation of methods accounting for population structure with pedigree data and continuous outcomes
Author(s) -
Peloso Gina M.,
Dupuis Josée,
Lunetta Kathryn L.
Publication year - 2011
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20590
Subject(s) - population , statistics , sample (material) , econometrics , sample size determination , principal component analysis , regression , range (aeronautics) , predictive power , mathematics , computer science , demography , engineering , philosophy , chromatography , sociology , aerospace engineering , chemistry , epistemology
Methods to account for population structure (PS) in genome‐wide association studies have been well developed in samples of unrelated individuals, but when a sample is composed of families, the task of finding and accounting for PS is not as straight forward. Family‐based tests that condition on parental genotypes or their sufficient statistics are immune to biases due to PS, but are known to have low power, particularly for unselected samples. Population‐based approaches that use all available data are an attractive alternative, but the methods have not been evaluated for continuous outcomes when a sample has both family and PS. Therefore, we compare through simulation the performance of population‐based regression models that account for family and PS with continuous outcomes using a range of family sizes and structures, including two and three generational families with admixed and discrete PS. We find that when computation time is a concern, the Dupuis et al. efficient score test performs very well. When computational time is not an issue, a linear mixed effects model adjusting for genetic principal components tends to have slightly better power than the score test and may be preferred. Genet. Epidemiol . 35:427–436, 2011. © 2011 Wiley‐Liss, Inc.