ArticleEuropean journal of human genetics : EJHG2009
Joint analysis of tightly linked SNPs in screening step of genome-wide association studies leads to increased power.
Article in European journal of human genetics : EJHG, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle.BMC genetics · 2019Article
- Genome-wide haplotypic testing in a Finnish cohort identifies a novel association with low-density lipoprotein cholesterol.European journal of human genetics : EJHG · 2015Article
- Effect of polymorphisms in the CSN3 (κ-casein) gene on milk production traits in Chinese Holstein Cattle.Molecular biology reports · 2014Article
- Power of single- vs. multi-marker tests of association.Genetic epidemiology · 2012Article
- A haplotype inference algorithm for trios based on deterministic sampling.BMC genetics · 2010Article
- Regression-based approach for testing the association between multi-region haplotype configuration and complex trait.BMC genetics · 2009Article
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2 authors.
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Abstract
Recent developments in genome-wide association studies (GWAS) have lead to the localization of disease genes for many complex diseases. The scrutiny of the respective publications reveals, first, that statistical analysis is restricted typically to single-marker analysis in the first step, and that, second, the presence of multiple, independently associated SNPs within the same linkage disequilibrium (LD) region is a common phenomenon. Motivated by this observation, we show through a power simulation study that a simultaneous analysis of tightly linked SNPs in the initial GWAS analysis step would lead to increased power, when compared with that in single-marker analysis. This is true for all the three approaches we considered (implementations in BEAGLE, FAMHAP and UNPHASED). The best performance was obtained using a two-marker haplotype analysis. In conclusion, we would expect additional gene findings for re-analyzing successful GWAS with a multi-marker approach.
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