File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: CLUMPHAP: A simple tool for performing haplotype-based association analysis

TitleCLUMPHAP: A simple tool for performing haplotype-based association analysis
Authors
KeywordsAssociation
Genetic
Haplotype clustering
Issue Date2008
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841
Citation
Genetic Epidemiology, 2008, v. 32 n. 6, p. 539-545 How to Cite?
AbstractThe 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 x2 statistic between each haplotype cluster and disease; the statistical significance of the largest of the x2 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 haplorpe test and is comparable in power to multiple regression locus-coding approaches. © 2008 Wiley-Liss, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/59699
ISSN
2023 Impact Factor: 1.7
2023 SCImago Journal Rankings: 0.977
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorKnight, Jen_HK
dc.contributor.authorCurtis, Den_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2010-05-31T03:55:40Z-
dc.date.available2010-05-31T03:55:40Z-
dc.date.issued2008en_HK
dc.identifier.citationGenetic Epidemiology, 2008, v. 32 n. 6, p. 539-545en_HK
dc.identifier.issn0741-0395en_HK
dc.identifier.urihttp://hdl.handle.net/10722/59699-
dc.description.abstractThe 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 x2 statistic between each haplotype cluster and disease; the statistical significance of the largest of the x2 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 haplorpe test and is comparable in power to multiple regression locus-coding approaches. © 2008 Wiley-Liss, Inc.en_HK
dc.languageengen_HK
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841en_HK
dc.relation.ispartofGenetic Epidemiologyen_HK
dc.rightsGenetic Epidemiology. Copyright © John Wiley & Sons, Inc.en_HK
dc.subjectAssociationen_HK
dc.subjectGeneticen_HK
dc.subjectHaplotype clusteringen_HK
dc.titleCLUMPHAP: A simple tool for performing haplotype-based association analysisen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0741-0395&volume=32&spage=539&epage=545&date=2008&atitle=CLUMPHAP:+A+Simple+Tool+for+Performing+Haplotype-based+Association+Analysisen_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/gepi.20327en_HK
dc.identifier.pmid18395815-
dc.identifier.scopuseid_2-s2.0-51749116888en_HK
dc.identifier.hkuros157988en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-51749116888&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume32en_HK
dc.identifier.issue6en_HK
dc.identifier.spage539en_HK
dc.identifier.epage545en_HK
dc.identifier.isiWOS:000258871100006-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridKnight, J=13002769800en_HK
dc.identifier.scopusauthoridCurtis, D=14633020700en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.citeulike2997263-
dc.identifier.issnl0741-0395-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats