Efficient multilocus association testing for whole genome association studies using localized haplotype clustering
Open accessAbstract
Whole genome association studies are generating data sets with hundreds of thousands of markers genotyped on thousands of cases and controls. We show that whole genome haplotypic association testing with permutation to account for multiple testing is statistically powerful and computationally feasible on such data, using an efficient software implementation of a recently proposed method. We use realistic simulations to explore the statistical properties of the method, and show that for ungenotyped disease‐susceptibility variants with population frequencies of 5% or less the haplotypic tests have markedly better power than single‐marker tests. We propose a combined single‐marker and haplotypic strategy, in which both single‐marker and haplotypic tests are applied, with the minimum P‐value adjusted for multiple testing by permutation which results in a test that is powerful for detecting both low‐and high‐frequency disease‐susceptibility variants. Genet. Epidemiol. 2007. © 2007 Wiley‐Liss, Inc.
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Genotype imputation used 1,000 Genomes and BEAGLE, and imputed SNPs with call rate below 95% or BEAGLE r2 at or below 0.3 were removed.
“Imputation was performed as described before (Cruchaga, et al., 2013). Briefly the 1,000 genome data and BEAGLE v3.3.1 (Browning and Browning, 2007) software were used to impute up to 6 million SNPs. SNPs with a call rate <95% or a BEAGLE r2 ≤0.3 were removed, leaving a total of 5,970,354 imputed and genotyped variants”
From A potential endophenotype for Alzheimer's disease: cerebrospinal fluid clusterin (2016) · cites this paper as Browning and Browning, 2007
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- Authors
- Browning, B. L., & Browning, S. R.
- Affiliations
- University of Auckland (NZ)
- Corresponding author
- Browning, Sharon R.
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2007-02-26
- Volume
- 31
- Issue
- 5
- Pages
- 365-375
- ISSN
- 0741-0395 (ISSN-L)
- 1098-2272
- OpenAlex
- W1979963342
- Cited by
- 162
- References
- 19
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1 · 2023: 10 · 2022: 5 · 2021: 3 · 2020: 6 · 2019: 9 · 2018: 6 · 2017: 7 · 2016: 6 · 2015: 13 · 2014: 20 · 2013: 14 · 2012: 12
- FWCI
- 6.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- GlaxoSmithKline
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Keywords
- haplotype association, whole-genome association studies, statistical power, low-frequency variants, computational efficiency
- MeSH terms
- Genetic Markers, Haplotypes, Humans, Models, Genetic, Models, Statistical, Linkage Disequilibrium, Genome, Human, Cluster Analysis, Molecular Epidemiology, Genetic Predisposition to Disease, Genomics
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