ArticleAmerican journal of human genetics2006
Improved power offered by a score test for linkage disequilibrium mapping of quantitative-trait loci by selective genotyping.
Article in American journal of human genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
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- Detecting rare variant effects using extreme phenotype sampling in sequencing association studies.Genetic epidemiology · 2013Article
- Analysis of case-control association studies with known risk variants.Bioinformatics (Oxford, England) · 2012Article
- Informed conditioning on clinical covariates increases power in case-control association studies.PLoS genetics · 2012Article
- Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.Genetic epidemiology · 2011Article
- A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.Behavior genetics · 2011Article
- Extremes of unexplained variation as a phenotype: an efficient approach for genome-wide association studies of cardiovascular disease.Circulation. Cardiovascular genetics · 2010Article
- Power of selective genotyping in genome-wide association studies of quantitative traits.BMC proceedings · 2009Article
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- A new association test to test multiple-marker association.Genetic epidemiology · 2009Article
- Genome-wide association analyses of quantitative traits: the GAW16 experience.Genetic epidemiology · 2009Article
- Testing for association on the X chromosome.Biostatistics (Oxford, England) · 2008Article
- An ensemble learning approach jointly modeling main and interaction effects in genetic association studies.Genetic epidemiology · 2008Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Selective genotyping is used to increase efficiency in genetic association studies of quantitative traits by genotyping only those individuals who deviate from the population mean. However, selection distorts the conditional distribution of the trait given genotype, and such data sets are usually analyzed using case-control methods, quantitative analysis within selected groups, or a combination of both. We show that Hotelling's T(2) test, recently proposed for association studies of one or several tagging single-nucleotide polymorphisms in a prospective (i.e., trait given genotype) design, can also be applied to the retrospective (i.e., genotype given trait) selective-genotyping design, and we use simulation to demonstrate its improved power over existing methods.
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