Use of weighted reference panels based on empirical estimates of ancestry for capturing untyped variation.
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ABSTRACT: Many association methods use a subset of genotyped single nucleotide polymorphisms (SNPs) to capture or infer genotypes at other untyped SNPs. We and others previously showed that tag SNPs selected to capture common variation using data from The International HapMap Consortium (Nature 437:1299-1320, 2005), The International HapMap Consortium (Nature 449:851-861, 2007) could also capture variation in populations of similar ancestry to HapMap reference populations (de Bakker et al. in Nat Genet 38:1298-1303, 2006; González-Neira et al. in Genome Res 16:323-330, 2006; Montpetit et al. in PLoS Genet 2:282-290, 2006; Mueller et al. in Am J Hum Genet 76:387-398, 2005). To capture variation in admixed populations or populations less similar to HapMap panels, a "cosmopolitan approach," in which all samples from HapMap are used as a single reference panel, was proposed. Here we refine this suggestion and show that use of a "weighted reference panel," constructed based on empirical estimates of ancestry in the target population (relative to available reference panels), is more efficient than the cosmopolitan approach. Weighted reference panels capture, on average, only slightly fewer common variants (minor allele frequency > 5%) than the cosmopolitan approach (mean r (2) = 0.977 vs. 0.989, 94.5% variation captured vs. 96.8% at r (2) > 0.8), across the five populations of the Multiethnic Cohort, but entail approximately 25% fewer tag SNPs per panel (average 538 vs. 718). These results extend a recent study in two Indian populations (Pemberton et al. in Ann Hum Genet 72:535-546, 2008). Weighted reference panels are potentially useful for both the selection of tag SNPs in diverse populations and perhaps in the design of reference panels for imputation of untyped genotypes in genome-wide association studies in admixed populations.
SUBMITTER: Egyud MR
PROVIDER: S-EPMC3126674 | biostudies-other | 2009 Apr
REPOSITORIES: biostudies-other
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