CLUMPHAP: a simple tool for performing haplotype‐based association analysis
Identifieur interne : 000E52 ( Main/Exploration ); précédent : 000E51; suivant : 000E53CLUMPHAP: a simple tool for performing haplotype‐based association analysis
Auteurs : Jo Knight [Royaume-Uni] ; David Curtis [Royaume-Uni] ; Pak C. Sham [Royaume-Uni, Hong Kong]Source :
- Genetic Epidemiology [ 0741-0395 ] ; 2008-09.
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Abstract
The completion of the HapMap Project and the development of high‐throughput single nucleotide polymorphism genotyping technologies have greatly enhanced the prospects of identifying and characterizing the genetic variants that influence complex traits. In principle, association analysis of haplotypes rather than single nucleotide polymorphisms may better capture an underlying causal variant, but the multiple haplotypes can lead to reduced statistical power due to the testing of (and need to correct for) a large number of haplotypes. This paper presents a novel method based on clustering similar haplotypes to address this issue. The method, implemented in the CLUMPHAP program, is an extension of the CLUMP program designed for the analysis of multi‐allelic markers (Sham and Curtis [1995] Ann. Hum. Genet. 59(Pt1):97–105). CLUMPHAP performs a hierarchical clustering of the haplotypes and then computes the χ2 statistic between each haplotype cluster and disease; the statistical significance of the largest of the χ2 statistics is obtained by permutation testing. A significant result suggests that the presence of a disease‐causing variant in the haplotype cluster is over‐represented in cases. Using simulation studies, we have compared CLUMPHAP and more widely used approaches in terms of their statistical power to identify an untyped susceptibility locus. Our results show that CLUMPHAP tends to have greater power than the omnibus haplotype test and is comparable in power to multiple regression locus‐coding approaches. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.
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DOI: 10.1002/gepi.20327
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Epidemiol.</title><idno type="ISSN">0741-0395</idno><idno type="eISSN">1098-2272</idno><imprint><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><pubPlace>Hoboken</pubPlace><date type="published" when="2008-09">2008-09</date><biblScope unit="volume">32</biblScope><biblScope unit="issue">6</biblScope><biblScope unit="page" from="539">539</biblScope><biblScope unit="page" to="545">545</biblScope></imprint><idno type="ISSN">0741-0395</idno></series><idno type="istex">566526948609100A7A6027552F7A698DB9250D43</idno><idno type="DOI">10.1002/gepi.20327</idno><idno type="ArticleID">GEPI20327</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0741-0395</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>association</term><term>genetic</term><term>haplotype clustering</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The completion of the HapMap Project and the development of high‐throughput single nucleotide polymorphism genotyping technologies have greatly enhanced the prospects of identifying and characterizing the genetic variants that influence complex traits. In principle, association analysis of haplotypes rather than single nucleotide polymorphisms may better capture an underlying causal variant, but the multiple haplotypes can lead to reduced statistical power due to the testing of (and need to correct for) a large number of haplotypes. This paper presents a novel method based on clustering similar haplotypes to address this issue. The method, implemented in the CLUMPHAP program, is an extension of the CLUMP program designed for the analysis of multi‐allelic markers (Sham and Curtis [1995] Ann. Hum. Genet. 59(Pt1):97–105). CLUMPHAP performs a hierarchical clustering of the haplotypes and then computes the χ2 statistic between each haplotype cluster and disease; the statistical significance of the largest of the χ2 statistics is obtained by permutation testing. A significant result suggests that the presence of a disease‐causing variant in the haplotype cluster is over‐represented in cases. Using simulation studies, we have compared CLUMPHAP and more widely used approaches in terms of their statistical power to identify an untyped susceptibility locus. Our results show that CLUMPHAP tends to have greater power than the omnibus haplotype test and is comparable in power to multiple regression locus‐coding approaches. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.</div></front></TEI><affiliations><list><country><li>Hong Kong</li><li>Royaume-Uni</li></country><region><li>Angleterre</li><li>Grand Londres</li></region><settlement><li>Londres</li></settlement></list><tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Knight, Jo" sort="Knight, Jo" uniqKey="Knight J" first="Jo" last="Knight">Jo Knight</name></region><name sortKey="Curtis, David" sort="Curtis, David" uniqKey="Curtis D" first="David" last="Curtis">David Curtis</name><name sortKey="Sham, Pak C" sort="Sham, Pak C" uniqKey="Sham P" first="Pak C." last="Sham">Pak C. 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