ArticleBMC genetics2006
Volume measures for linkage disequilibrium.
Article in BMC genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Article
- Forensic applications and genetic characterization of Liaoning Han population revealed by extended set of autosomal STRs.Molecular genetics & genomic medicine · 2020Article
- Genetic Loci Controlling Carotenoid Biosynthesis in Diverse Tropical Maize Lines.G3 (Bethesda, Md.) · 2018Article
- Effective Population Size and Signatures of Selection Using Bovine 50K SNP Chips in Korean Native Cattle (Hanwoo).Evolutionary bioinformatics online · 2015Article
- Genetic Structure of and Evidence for Admixture between Western and Korean Native Pig Breeds Revealed by Single Nucleotide Polymorphisms.Asian-Australasian journal of animal sciences · 2014Article
- Linkage Disequilibrium Estimation of Chinese Beef Simmental Cattle Using High-density SNP Panels.Asian-Australasian journal of animal sciences · 2013Article
- Population-genetic comparison of the Sorbian isolate population in Germany with the German KORA population using genome-wide SNP arrays.BMC genetics · 2011Article
- Haplotype block partitioning as a tool for dimensionality reduction in SNP association studies.BMC genomics · 2008Article
- Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel.BMC genomics · 2008Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundDefining measures of linkage disequilibrium (LD) that have good small sample properties and are applicable to multiallelic markers poses some challenges. The potential of volume measures in this context has been noted before, but their use has been hampered by computational challenges.
resultsWe design a sequential importance sampling algorithm to evaluate volume measures on I x J tables. The algorithm is implemented in a C routine as a complement to exhaustive enumeration. We make the C code available as open source. We achieve fast and accurate evaluation of volume measures in two dimensional tables.
conclusionApplying our code to simulated and real datasets reinforces the belief that volume measures are a very useful tool for LD evaluation: they are not inflated in small samples, their definition encompasses multiallelic markers, and they can be computed with appreciable speed.
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