Literature DB >> 17508341

Comparison of admixture and association mapping in admixed families.

Geraldine Clarke1, Alice S Whittemore.   

Abstract

The family-based admixture mapping test (AMT) identifies disease-related genes using family data from admixed individuals with the disease of interest (cases). The cases' genotypes at a set of markers are used to infer their DNA ancestry as it varies in blocks along the chromosomes. The test compares the cases' inferred ancestries to those expected from their family histories. Deviation between observed and expected ancestries in a region suggests the presence of a disease gene. We use a likelihood-based development of the AMT to compare it with the transmission disequilibrium test (TDT) as applied to admixed populations. The two tests have a common framework but differ significantly when the disease locus is untyped. The TDT infers disease-locus genotypes using the markers with which it is in linkage disequilibrium (LD). In contrast, the AMT infers disease locus ancestries using those of its linked markers. Thus, TDT power depends on LD between disease and marker loci, while AMT power depends on the lengths of the ancestry blocks containing the disease locus. We compare the power of the two tests when applied to cases with descent from two ancestral populations. The AMT outperforms the TDT when case marker ancestries are correctly specified and LD between disease and marker loci is less than one-third its maximal value (Delta' < 1/3). However, the TDT performs better in the presence of uncertain marker ancestries, even for weak LD between disease and marker loci (Delta' = 0.1). These findings have implications for the design of studies using admixed populations.

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Year:  2007        PMID: 17508341     DOI: 10.1002/gepi.20239

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  3 in total

1.  Joint testing of genotype and ancestry association in admixed families.

Authors:  Hua Tang; David O Siegmund; Nicholas A Johnson; Isabelle Romieu; Stephanie J London
Journal:  Genet Epidemiol       Date:  2010-12       Impact factor: 2.135

Review 2.  Review and evaluation of methods correcting for population stratification with a focus on underlying statistical principles.

Authors:  Hemant K Tiwari; Jill Barnholtz-Sloan; Nathan Wineinger; Miguel A Padilla; Laura K Vaughan; David B Allison
Journal:  Hum Hered       Date:  2008-03-31       Impact factor: 0.444

3.  Genome-wide association study implicates chromosome 9q21.31 as a susceptibility locus for asthma in mexican children.

Authors:  Dana B Hancock; Isabelle Romieu; Min Shi; Juan-Jose Sienra-Monge; Hao Wu; Grace Y Chiu; Huiling Li; Blanca Estela del Rio-Navarro; Saffron A G Willis-Owen; Saffron A G Willis-Owens; Scott T Weiss; Benjamin A Raby; Hong Gao; Celeste Eng; Rocio Chapela; Esteban G Burchard; Hua Tang; Patrick F Sullivan; Stephanie J London
Journal:  PLoS Genet       Date:  2009-08-28       Impact factor: 5.917

  3 in total

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