Power of Linkage versus Association Analysis of Quantitative Traits, by Use of Variance-Components Models, for Sibship Data
Open accessAbstract
Optimal design of quantitative-trait loci (QTL) mapping studies requires a precise understanding of the power of QTL linkage versus QTL association analysis, under a range of different conditions. In this article, we investigate the power of QTL linkage and association analyses for simple random sibship samples, under the variance-components model proposed by Fulker et al. After a brief description of an extension of this variance-components model, we show that the powers of both linkage and association analyses are crucially dependent on the proportion of phenotypic variance attributable to the QTL. The main difference between the two tests is that, whereas the power of association is directly related to the QTL heritability, the power of linkage is related more closely to the square of the QTL heritability. We also describe both how the power of linkage is attenuated by incomplete linkage and incomplete marker information and how the power of association is attenuated by incomplete linkage disequilibrium.
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GWAS favor the discovery of genetic variants that are common in the study population.
“1) GWAS favor the discovery of genetic variants that are common in the study population;”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [29]
The paper’s opening summary (p. 1616) says association-analysis power depends on the proportion of phenotypic variance attributable to a QTL, and its variance formula includes the QTL alleles’ population frequencies. That is consistent with frequency affecting detection power, but the paper studies sibship-based QTL analysis and does not establish the broader claim that GWAS preferentially discover common variants. (LLM, conf=0.74)
Experimental — accuracy not yet measuredThe power to discover an association in a genetic study depends on the effect size and frequency of the variant.
“First, the power to discover an association in a genetic study depends on the effect size and frequency of the variant29.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [29]
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Cites
LINKAGE DISEQUILIBRIUM AT STEADY STATE DETERMINED BY RANDOM GENETIC DRIFT AND RECURRENT MUTATION
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Clinical use of current polygenic risk scores may exacerbate health disparities
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Self-citationStatistical power and significance testing in large-scale genetic studies
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Genetic approaches to stature, pubertal timing, and other complex traits
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- Authors
- Sham, P. C., Cherny, S. S., Purcell, S., & Hewitt, J. K.
- Affiliations
- King's College London (GB)
- University of Colorado Boulder (US)
- Corresponding author
- Sham, P.C.
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2000-05
- Volume
- 66
- Issue
- 5
- Pages
- 1616-1630
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC1378020
- OpenAlex
- W1979164118
- Cited by
- 260
- References
- 1
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 1 · 2022: 3 · 2021: 3 · 2020: 6 · 2019: 5 · 2018: 10 · 2017: 5 · 2016: 3 · 2015: 4 · 2014: 7 · 2013: 6 · 2012: 8
- FWCI
- 11.51
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- Wellcome Trust
- National Institutes of Health (5r01aa007330-12)
- Medical Research Council
- National Institute on Alcohol Abuse and Alcoholism (AA10556, AA-07330)
- National Eye Institute (EY12562, R01EY012562)
- 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 › Genetic and phenotypic traits in livestock
- Keywords
- QTL mapping, linkage analysis, association analysis, statistical power, variance component models, linkage disequilibrium, quantitative traits
- MeSH terms
- Chromosome Mapping, Computer Simulation, Gene Frequency, Genetic Markers, Genotype, Haplotypes, Humans, Lod Score, Models, Genetic, Nuclear Family, Genetic Variation, Linkage Disequilibrium, Chi-Square Distribution, Likelihood Functions, Matched-Pair Analysis, Sample Size, Quantitative Trait, Heritable
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