ArticleAmerican journal of human genetics2006
A fine-scale linkage-disequilibrium measure based on length of haplotype sharing.
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 9 papers.
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Who cites it
9 citing papers in PubMed.
- TIGA: target illumination GWAS analytics.Bioinformatics (Oxford, England) · 2021Article
- MyD88 Polymorphisms and Association with Susceptibility to Salmonella Pullorum.BioMed research international · 2015Article
- Composite likelihood-based inferences on genetic data from dependent loci.Journal of mathematical biology · 2011Article
- A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.Bioinformatics (Oxford, England) · 2010Article
- A multilocus linkage disequilibrium measure based on mutual information theory and its applications.Genetica · 2009Article
- Correcting estimators of theta and Tajima's D for ascertainment biases caused by the single-nucleotide polymorphism discovery process.Genetics · 2009Article
- Haplotype block partitioning as a tool for dimensionality reduction in SNP association studies.BMC genomics · 2008Article
- Parallel selection on TRPV6 in human populations.PloS one · 2008Article
- PLINK: a tool set for whole-genome association and population-based linkage analyses.American journal of human genetics · 2007Article
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Authors and funding
3 authors.
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Abstract
High-throughput genotyping technologies for SNPs have enabled the recent completion of the International HapMap Project (phase I), which has stimulated much interest in studying genomewide linkage-disequilibrium (LD) patterns. Conventional LD measures, such as D' and r(2), are two-point measurements, and their relationship with physical distance is highly noisy. We propose a new LD measure, Delta , defined in terms of the correlation coefficient for shared haplotype lengths around two loci, thereby borrowing information from multiple loci. A U-statistic-based estimator of Delta , which takes into consideration the dependence structure of the observed data, is developed and compared with an estimator based on the usual empirical correlation coefficient. Furthermore, we propose methods for inferring LD-decay rates and recombination hotspots on the basis of Delta . The results from coalescent-simulation studies and analysis of HapMap SNP data demonstrate that the proposed estimators of Delta are superior to the two most popular conventional LD measures, in terms of their close relationship with physical distance and recombination rate, their small variability, and their strong robustness to marker-allele frequencies. These merits may offer new opportunities for mapping complex disease genes and for investigating recombination mechanisms on the basis of better-quantified LD.
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