ArticleBMC genetics2004
Comparison of the accuracy of methods of computational haplotype inference using a large empirical dataset.
Article in BMC genetics, 2004. 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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21 citing papers in PubMed, 70 citations in OpenAlex.
- Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples.Malaria journal · 2021Article
- Markov chain Monte Carlo and expectation maximization approaches for estimation of haplotype frequencies for multiply infected human blood samples.Malaria journal · 2016Article
- Matrix Gla protein (MGP) promoter polymorphic variants and its serum level in stenosis of coronary artery.Molecular biology reports · 2014Article
- Nuclear gene phylogeography using PHASE: dealing with unresolved genotypes, lost alleles, and systematic bias in parameter estimation.BMC evolutionary biology · 2010Article
- Polymorphisms in CRHR1 and the serotonin transporter loci: gene x gene x environment interactions on depressive symptoms.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2010Article
- Role of in silico tools in gene discovery.Molecular biotechnology · 2009Review
- Shape-IT: new rapid and accurate algorithm for haplotype inference.BMC bioinformatics · 2008Article
- Nucleotide excision repair genes and risk of lung cancer among San Francisco Bay Area Latinos and African Americans.International journal of cancer · 2008Article
- A model of higher accuracy for the individual haplotyping problem based on weighted SNP fragments and genotype with errors.Bioinformatics (Oxford, England) · 2008Article
- Haplotype reconstruction error as a classical misclassification problem: introducing sensitivity and specificity as error measures.PloS one · 2008Article
- Evaluation of two methods for computational HLA haplotypes inference using a real dataset.BMC bioinformatics · 2008Article
- Study of association between common variation in the insulin-like growth factor 2 gene and indices of obesity and body size in middle-aged men and women.The Journal of clinical endocrinology and metabolism · 2007Article
- ISHAPE: new rapid and accurate software for haplotyping.BMC bioinformatics · 2007Article
- Arlequin (version 3.0): an integrated software package for population genetics data analysis.Evolutionary bioinformatics online · 2007Article
- Computation of haplotypes on SNPs subsets: advantage of the "global method".BMC genetics · 2006Article
- Are molecular haplotypes worth the time and expense? A cost-effective method for applying molecular haplotypes.PLoS genetics · 2006Article
- High-throughput genomic technology in research and clinical management of breast cancer. Evolving landscape of genetic epidemiological studies.Breast cancer research : BCR · 2006Review
- Accuracy of haplotype estimation in a region of low linkage disequilibrium.BMC genetics · 2005Article
- Polymorphisms in cinnamoyl CoA reductase (CCR) are associated with variation in microfibril angle in Eucalyptus spp.Genetics · 2005Article
- Shotgun haplotyping: a novel method for surveying allelic sequence variation.Nucleic acids research · 2005Article
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1 author at 1 institution in 1 country.
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Abstract
backgroundAnalyses of genetic data at the level of haplotypes provide increased accuracy and power to infer genotype-phenotype correlations and evolutionary history of a locus. However, empirical determination of haplotypes is expensive and laborious. Therefore, several methods of inferring haplotypes from unphased genotypic data have been proposed, but it is unclear how accurate each of the methods is or which methods are superior. The accuracy of some of the leading methods of computational haplotype inference (PL-EM, Phase, SNPHAP, Haplotyper) are compared using a large set of 308 empirically determined haplotypes based on 15 SNPs, among which 36 haplotypes were observed to occur. This study presents several advantages over many previous comparisons of haplotype inference methods: a large number of subjects are included, the number of known haplotypes is much smaller than the number of chromosomes surveyed, a range in values of linkage disequilibrium, presence of rare SNP alleles, and considerable dispersion in the frequencies of haplotypes.
resultsIn contrast to some previous comparisons of haplotype inference methods, there was very little difference in the accuracy of the various methods in terms of either assignment of haplotypes to individuals or estimation of haplotype frequencies. Although none of the methods inferred all of the known haplotypes, the assignment of haplotypes to subjects was about 90% correct for individuals heterozygous for up to three SNPs and was about 80% correct for up to five heterozygous sites. All of the methods identified every haplotype with a frequency above 1%, and none assigned a frequency above 1% to an incorrect haplotype.
conclusionsAll of the methods of haplotype inference have high accuracy and one can have confidence in inferences made by any one of the methods. The ability to identify even rare (>/= 1%) haplotypes is reassuring for efforts to identify haplotypes that contribute to disease in a significant proportion of a population. Assignment of haplotypes is relatively accurate among subjects heterozygous for up to 5 sites, and this might be the largest number of SNPs for which one should define haplotype blocks or have confidence in haplotype assignments.
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