ArticleHuman genetics2003
Entropy-based SNP selection for genetic association studies.
Article in Human genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Research on multi-trait genome association study method based on Shannon information entropy.BMC bioinformatics · 2026Article
- Estimating Sentence-like Structure in Synthetic Languages Using Information Topology.Entropy (Basel, Switzerland) · 2022Article
- An Information Theoretic Approach to Symbolic Learning in Synthetic Languages.Entropy (Basel, Switzerland) · 2022Article
- An adaptive strategy for association analysis of common or rare variants using entropy theory.Journal of human genetics · 2017Article
- Article
- Analysis and optimization of bulk DNA sampling with binary scoring for germplasm characterization.PloS one · 2013Article
- Genetic association studies: an information content perspective.Current genomics · 2012Article
- Sequential Support Vector Regression with Embedded Entropy for SNP Selection and Disease Classification.Statistical analysis and data mining · 2011Article
- Probability theory-based SNP association study method for identifying susceptibility loci and genetic disease models in human case-control data.IEEE transactions on nanobioscience · 2010Article
- Efficient genome-wide TagSNP selection across populations via the linkage disequilibrium criterion.Journal of computational biology : a journal of computational molecular cell biology · 2010Article
- Gene-centric genomewide association study via entropy.Genetics · 2008Article
- Prioritize and select SNPs for association studies with multi-stage designs.Journal of computational biology : a journal of computational molecular cell biology · 2008Article
- Supervised learning-based tagSNP selection for genome-wide disease classifications.BMC genomics · 2008Article
- An entropy-based genome-wide transmission/disequilibrium test.Human genetics · 2007Article
- Efficacy assessment of SNP sets for genome-wide disease association studies.Nucleic acids research · 2007Article
- Entropy-based joint analysis for two-stage genome-wide association studies.Journal of human genetics · 2007Article
- A sparse marker extension tree algorithm for selecting the best set of haplotype tagging single nucleotide polymorphisms.Genetic epidemiology · 2005Article
- An entropy-based statistic for genomewide association studies.American journal of human genetics · 2005Article
- Finding haplotype tagging SNPs by use of principal components analysis.American journal of human genetics · 2004Article
- Optimal haplotype block-free selection of tagging SNPs for genome-wide association studies.Genome research · 2004Article
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3 authors.
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Abstract
Because of their abundance, density, and ease of practical use, single-nucleotide polymorphisms (SNPs) have become the major source of information for association gene mapping in humans. Sensible strategies for selecting practically useful SNPs are therefore required. Among the factors influencing the mapping utility of a given set of SNPs are (1). their individual diversity, (2). their haplotype structure in the population of interest, and (3). their physical distribution. We propose a strategy integrating these aspects into a single mapping utility measure, which is based upon Shannon entropy, and which maximizes the amount of information extracted from a genomic region under a Malecot model of linkage disequilibrium (LD) decay. The same utility measure has also been used to define a criterion guiding SNP discovery and rational decision-making about the continuation or termination of a mapping study. The proposed strategy performs consistently well in a data set comprising 549 German control individuals, genotyped for 136 SNPs from four genomic regions of different LD structure. Adoption of the method in practice is estimated to save up to 30% of genotyping load when compared with equidistant SNP localization or pair-wise LD minimization alone.
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