ArticleGenome research2004
Optimal haplotype block-free selection of tagging SNPs for genome-wide association studies.
Article in Genome research, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 136 citations in OpenAlex.
- Increasing the number of SNP loci does not necessarily improve prediction power at least in the comparison of MTHFR SNP and haplotypes.Journal of epidemiology · 2008Trial
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- Informative SNP Selection Based on a Fuzzy Clustering and Improved Binary Particle Swarm Optimization Algorithm.Computational and mathematical methods in medicine · 2022Article
- InPhaDel: integrative shotgun and proximity-ligation sequencing to phase deletions with single nucleotide polymorphisms.Nucleic acids research · 2016Article
- A steroid metabolizing gene variant in a polyfactorial model improves risk prediction in a high incidence breast cancer population.BBA clinical · 2014Article
- Identifying large sets of unrelated individuals and unrelated markers.Source code for biology and medicine · 2014Article
- The utility of low-density genotyping for imputation in the Thoroughbred horse.Genetics, selection, evolution : GSE · 2014Article
- Genetic association studies: an information content perspective.Current genomics · 2012Article
- Genome-wide association filtering using a highly locus-specific transmission/disequilibrium test.Human genetics · 2010Article
- FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium.BMC bioinformatics · 2010Article
- CGTS: a site-clustering graph based tagSNP selection algorithm in genotype data.BMC bioinformatics · 2009Article
- Supervised learning-based tagSNP selection for genome-wide disease classifications.BMC genomics · 2008Article
- Effective selection of informative SNPs and classification on the HapMap genotype data.BMC bioinformatics · 2007Article
- Intra- and interpopulation genotype reconstruction from tagging SNPs.Genome research · 2007Article
- Nonlinear tests for genomewide association studies.Genetics · 2006Article
- A model-based approach to selection of tag SNPs.BMC bioinformatics · 2006Article
- Using high-throughput SNP technologies to study cancer.Oncogene · 2006Review
- Analysis of concordance of different haplotype block partitioning algorithms.BMC bioinformatics · 2005Article
- A sparse marker extension tree algorithm for selecting the best set of haplotype tagging single nucleotide polymorphisms.Genetic epidemiology · 2005Article
- Selecting additional tag SNPs for tolerating missing data in genotyping.BMC bioinformatics · 2005Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is widely hoped that the study of sequence variation in the human genome will provide a means of elucidating the genetic component of complex diseases and variable drug responses. A major stumbling block to the successful design and execution of genome-wide disease association studies using single-nucleotide polymorphisms (SNPs) and linkage disequilibrium is the enormous number of SNPs in the human genome. This results in unacceptably high costs for exhaustive genotyping and presents a challenging problem of statistical inference. Here, we present a new method for optimally selecting minimum informative subsets of SNPs, also known as "tagging" SNPs, that is efficient for genome-wide selection. We contrast this method to published methods including haplotype block tagging, that is, grouping SNPs into segments of low haplotype diversity and typing a subset of the SNPs that can discriminate all common haplotypes within the blocks. Because our method does not rely on a predefined haplotype block structure and makes use of the weaker correlations that occur across neighboring blocks, it can be effectively applied across chromosomal regions with both high and low local linkage disequilibrium. We show that the number of tagging SNPs selected is substantially smaller than previously reported using block-based approaches and that selecting tagging SNPs optimally can result in a two- to threefold savings over selecting random SNPs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.