Literature DB >> 15077198

Little loss of information due to unknown phase for fine-scale linkage-disequilibrium mapping with single-nucleotide-polymorphism genotype data.

A P Morris1, J C Whittaker, D J Balding.   

Abstract

We present the results of a simulation study that indicate that true haplotypes at multiple, tightly linked loci often provide little extra information for linkage-disequilibrium fine mapping, compared with the information provided by corresponding genotypes, provided that an appropriate statistical analysis method is used. In contrast, a two-stage approach to analyzing genotype data, in which haplotypes are inferred and then analyzed as if they were true haplotypes, can lead to a substantial loss of information. The study uses our COLDMAP software for fine mapping, which implements a Markov chain-Monte Carlo algorithm that is based on the shattered coalescent model of genetic heterogeneity at a disease locus. We applied COLDMAP to 100 replicate data sets simulated under each of 18 disease models. Each data set consists of haplotype pairs (diplotypes) for 20 SNPs typed at equal 50-kb intervals in a 950-kb candidate region that includes a single disease locus located at random. The data sets were analyzed in three formats: (1). as true haplotypes; (2). as haplotypes inferred from genotypes using an expectation-maximization algorithm; and (3). as unphased genotypes. On average, true haplotypes gave a 6% gain in efficiency compared with the unphased genotypes, whereas inferring haplotypes from genotypes led to a 20% loss of efficiency, where efficiency is defined in terms of root mean integrated square error of the location of the disease locus. Furthermore, treating inferred haplotypes as if they were true haplotypes leads to considerable overconfidence in estimates, with nominal 50% credibility intervals achieving, on average, only 19% coverage. We conclude that (1). given appropriate statistical analyses, the costs of directly measuring haplotypes will rarely be justified by a gain in the efficiency of fine mapping and that (2). a two-stage approach of inferring haplotypes followed by a haplotype-based analysis can be very inefficient for fine mapping, compared with an analysis based directly on the genotypes.

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Year:  2004        PMID: 15077198      PMCID: PMC1181987          DOI: 10.1086/420773

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  14 in total

1.  Assessment of linkage disequilibrium by the decay of haplotype sharing, with application to fine-scale genetic mapping.

Authors:  M S McPeek; A Strahs
Journal:  Am J Hum Genet       Date:  1999-09       Impact factor: 11.025

2.  A new statistical method for haplotype reconstruction from population data.

Authors:  M Stephens; N J Smith; P Donnelly
Journal:  Am J Hum Genet       Date:  2001-03-09       Impact factor: 11.025

3.  Experimentally-derived haplotypes substantially increase the efficiency of linkage disequilibrium studies.

Authors:  J A Douglas; M Boehnke; E Gillanders; J M Trent; S B Gruber
Journal:  Nat Genet       Date:  2001-08       Impact factor: 38.330

4.  Fine-scale mapping of disease loci via shattered coalescent modeling of genealogies.

Authors:  A P Morris; J C Whittaker; D J Balding
Journal:  Am J Hum Genet       Date:  2002-02-08       Impact factor: 11.025

5.  Intensely punctate meiotic recombination in the class II region of the major histocompatibility complex.

Authors:  A J Jeffreys; L Kauppi; R Neumann
Journal:  Nat Genet       Date:  2001-10       Impact factor: 38.330

6.  Chromosome-wide distribution of haplotype blocks and the role of recombination hot spots.

Authors:  M S Phillips; R Lawrence; R Sachidanandam; A P Morris; D J Balding; M A Donaldson; J F Studebaker; W M Ankener; S V Alfisi; F-S Kuo; A L Camisa; V Pazorov; K E Scott; B J Carey; J Faith; G Katari; H A Bhatti; J M Cyr; V Derohannessian; C Elosua; A M Forman; N M Grecco; C R Hock; J M Kuebler; J A Lathrop; M A Mockler; E P Nachtman; S L Restine; S A Varde; M J Hozza; C A Gelfand; J Broxholme; G R Abecasis; M T Boyce-Jacino; L R Cardon
Journal:  Nat Genet       Date:  2003-02-18       Impact factor: 38.330

7.  A comparison of bayesian methods for haplotype reconstruction from population genotype data.

Authors:  Matthew Stephens; Peter Donnelly
Journal:  Am J Hum Genet       Date:  2003-10-20       Impact factor: 11.025

8.  Linkage disequilibrium mapping identifies a 390 kb region associated with CYP2D6 poor drug metabolising activity.

Authors:  L K Hosking; P R Boyd; C F Xu; M Nissum; K Cantone; I J Purvis; R Khakhar; M R Barnes; U Liberwirth; K Hagen-Mann; M G Ehm; J H Riley
Journal:  Pharmacogenomics J       Date:  2002       Impact factor: 3.550

9.  Haplotype information and linkage disequilibrium mapping for single nucleotide polymorphisms.

Authors:  Xin Lu; Tianhua Niu; Jun S Liu
Journal:  Genome Res       Date:  2003-09       Impact factor: 9.043

10.  Bayesian analysis of haplotypes for linkage disequilibrium mapping.

Authors:  J S Liu; C Sabatti; J Teng; B J Keats; N Risch
Journal:  Genome Res       Date:  2001-10       Impact factor: 9.043

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  27 in total

1.  Finding haplotype tagging SNPs by use of principal components analysis.

Authors:  Zhen Lin; Russ B Altman
Journal:  Am J Hum Genet       Date:  2004-09-23       Impact factor: 11.025

2.  An empirical comparison of case-control and trio based study designs in high throughput association mapping.

Authors:  P Hintsanen; P Sevon; P Onkamo; L Eronen; H Toivonen
Journal:  J Med Genet       Date:  2005-10-28       Impact factor: 6.318

3.  The role of pedigree information in combined linkage disequilibrium and linkage mapping of quantitative trait loci in a general complex pedigree.

Authors:  S H Lee; J H J Van der Werf
Journal:  Genetics       Date:  2005-01       Impact factor: 4.562

4.  Coalescent-based association mapping and fine mapping of complex trait loci.

Authors:  Sebastian Zöllner; Jonathan K Pritchard
Journal:  Genetics       Date:  2004-10-16       Impact factor: 4.562

5.  The impact of using related individuals for haplotype reconstruction in population studies.

Authors:  Michael T Schouten; Christopher K I Williams; Chris S Haley
Journal:  Genetics       Date:  2005-06-08       Impact factor: 4.562

6.  Combining the meiosis Gibbs sampler with the random walk approach for linkage and association studies with a general complex pedigree and multimarker loci.

Authors:  S H Lee; J H J Van der Werf; B Tier
Journal:  Genetics       Date:  2005-06-18       Impact factor: 4.562

7.  Simultaneous fine mapping of multiple closely linked quantitative trait Loci using combined linkage disequilibrium and linkage with a general pedigree.

Authors:  S H Lee; J H J Van der Werf
Journal:  Genetics       Date:  2006-06-04       Impact factor: 4.562

Review 8.  Haplotype thinking in lung disease.

Authors:  Edwin K Silverman
Journal:  Proc Am Thorac Soc       Date:  2007-01

9.  Power and precision of alternate methods for linkage disequilibrium mapping of quantitative trait loci.

Authors:  H H Zhao; R L Fernando; J C M Dekkers
Journal:  Genetics       Date:  2007-02-04       Impact factor: 4.562

10.  Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution.

Authors:  S H Lee; J H J Van der Werf
Journal:  Genetics       Date:  2006-09-01       Impact factor: 4.562

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