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Article: Design and analysis of association studies using pooled DNA from large twin samples

TitleDesign and analysis of association studies using pooled DNA from large twin samples
Authors
KeywordsAssociation
Micro-arrays
Pooling
Power
Statistical methodology
Twins
Issue Date2006
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244
Citation
Behavior Genetics, 2006, v. 36 n. 5, p. 665-677 How to Cite?
AbstractEvidence is mounting that multiple genes are involved in complex traits and that these each account for very small proportions of the overall phenotypic variance. Association studies of many markers in 1000s of individuals will be required to identify such genes. A number of large twin cohorts have already been collected and provide a valuable resource for carrying out studies that are robust to the effect of population stratification. Technologies based on microarrays will soon allow 1,000,000 SNPs to be typed at one time, however financial considerations prevent most researchers from using these approaches to genotype all individuals. Recently, microarrays have been shown to give accurate allele frequency measurements in pooled DNA samples and provide a simple way to select the best markers for individual genotyping. This drastically reduces the cost and workload of large scale association studies. One limitation of this methodology relates to the analytical procedures which have only been developed to allow comparison of two pools e.g. case/control pools. In this paper we use meta-regression to analyze pooled DNA data allowing the allele frequency in each pool to be related to the average quantitative phenotypic measure of the individuals whose DNA were used to construct the pools. Alongside this we describe a technique that can be used to determine the power for such studies. We present results from some preliminary investigations of different pooling strategies that can be applied to large twin samples and demonstrate that the method retains a large proportion of the power available from individual genotyping. © 2006 Springer Science+Business Media, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/81521
ISSN
2015 Impact Factor: 3.268
2015 SCImago Journal Rankings: 1.457
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorKnight, Jen_HK
dc.contributor.authorSham, Pen_HK
dc.date.accessioned2010-09-06T08:18:47Z-
dc.date.available2010-09-06T08:18:47Z-
dc.date.issued2006en_HK
dc.identifier.citationBehavior Genetics, 2006, v. 36 n. 5, p. 665-677en_HK
dc.identifier.issn0001-8244en_HK
dc.identifier.urihttp://hdl.handle.net/10722/81521-
dc.description.abstractEvidence is mounting that multiple genes are involved in complex traits and that these each account for very small proportions of the overall phenotypic variance. Association studies of many markers in 1000s of individuals will be required to identify such genes. A number of large twin cohorts have already been collected and provide a valuable resource for carrying out studies that are robust to the effect of population stratification. Technologies based on microarrays will soon allow 1,000,000 SNPs to be typed at one time, however financial considerations prevent most researchers from using these approaches to genotype all individuals. Recently, microarrays have been shown to give accurate allele frequency measurements in pooled DNA samples and provide a simple way to select the best markers for individual genotyping. This drastically reduces the cost and workload of large scale association studies. One limitation of this methodology relates to the analytical procedures which have only been developed to allow comparison of two pools e.g. case/control pools. In this paper we use meta-regression to analyze pooled DNA data allowing the allele frequency in each pool to be related to the average quantitative phenotypic measure of the individuals whose DNA were used to construct the pools. Alongside this we describe a technique that can be used to determine the power for such studies. We present results from some preliminary investigations of different pooling strategies that can be applied to large twin samples and demonstrate that the method retains a large proportion of the power available from individual genotyping. © 2006 Springer Science+Business Media, Inc.en_HK
dc.languageengen_HK
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244en_HK
dc.relation.ispartofBehavior Geneticsen_HK
dc.subjectAssociationen_HK
dc.subjectMicro-arraysen_HK
dc.subjectPoolingen_HK
dc.subjectPoweren_HK
dc.subjectStatistical methodologyen_HK
dc.subjectTwinsen_HK
dc.titleDesign and analysis of association studies using pooled DNA from large twin samplesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0001-8244&volume=36&issue=5&spage=665&epage=677&date=2006&atitle=Design+and+analysis+of+association+studies+using+pooled+DNA+from+large+twin+samplesen_HK
dc.identifier.emailSham, P: pcsham@hku.hken_HK
dc.identifier.authoritySham, P=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10519-005-9016-9en_HK
dc.identifier.pmid16479323-
dc.identifier.scopuseid_2-s2.0-33746896575en_HK
dc.identifier.hkuros134288en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33746896575&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume36en_HK
dc.identifier.issue5en_HK
dc.identifier.spage665en_HK
dc.identifier.epage677en_HK
dc.identifier.isiWOS:000239589700005-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridKnight, J=13002769800en_HK
dc.identifier.scopusauthoridSham, P=34573429300en_HK
dc.identifier.citeulike2447588-

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