ArticleGenetic epidemiology2012
Power of single- vs. multi-marker tests of association.
Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Comparative evaluation of GWAS-prioritized SNP, SSR, and insertion-type structural variant marker panels for genomic prediction in soybean.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Multi-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.Scientific reports · 2025Article
- Genome-wide iterative fine-mapping for non-Gaussian phenotypes.Scientific reports · 2025Article
- Utilizing Variants Identified with Multiple Genome-Wide Association Study Methods Optimizes Genomic Selection for Growth Traits in Pigs.Animals : an open access journal from MDPI · 2023Article
- Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.Journal of experimental botany · 2019Article
- Detecting genetic association through shortest paths in a bidirected graph.Genetic epidemiology · 2017Article
- Pentraxin 3, ficolin-2 and lectin pathway associated serine protease MASP-3 as early predictors of myocardial infarction - the HUNT2 study.Scientific reports · 2017Article
- Comparison of single-marker and multi-marker tests in rare variant association studies of quantitative traits.PloS one · 2017Article
- Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study: principal components analysis vs. partial least squares.Journal of biomedical research · 2015Article
- Family-based association analysis: a fast and efficient method of multivariate association analysis with multiple variants.BMC bioinformatics · 2015Article
- Fine-mapping additive and dominant SNP effects using group-LASSO and fractional resample model averaging.Genetic epidemiology · 2015Article
- Effect of polymorphisms in the CSN3 (κ-casein) gene on milk production traits in Chinese Holstein Cattle.Molecular biology reports · 2014Article
- Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: a haplotype-based analysis with penalized logistic regression.Genetic epidemiology · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Current genome-wide association studies still heavily rely on a single-marker strategy, in which each single nucleotide polymorphism (SNP) is tested individually for association with a phenotype. Although methods and software packages that consider multimarker models have become available, they have been slow to become widely adopted and their efficacy in real data analysis is often questioned. Based on conducting extensive simulations, here we endeavor to provide more insights into the performance of simple multimarker association tests as compared to single-marker tests. The results reveal the power advantage as well as disadvantage of the two- vs. the single-marker test. Power differentials depend on the correlation structure among tag SNPs, as well as that between tag SNPs and causal variants. A two-marker test has relatively better performance than single-marker tests when the correlation of the two adjacent markers is high. However, using HapMap data, two-marker tests tended to have a greater chance of being less powerful than single-marker tests, due to constraints on the number of actual possible haplotypes in the HapMap data. Yet, the average power difference was small whenever the one-marker test is more powerful, while there were many situations where the two-marker test can be much more powerful. These findings can be useful to guide analyses of future studies.
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