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Article: PLINK: A tool set for whole-genome association and population-based linkage analyses

TitlePLINK: A tool set for whole-genome association and population-based linkage analyses
Authors
Issue Date2007
PublisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
Citation
American Journal Of Human Genetics, 2007, v. 81 n. 3, p. 559-575 How to Cite?
AbstractWhole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis. © 2007 by The American Society of Human Genetics. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/81557
ISSN
2014 Impact Factor: 10.931
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorPurcell, Sen_HK
dc.contributor.authorNeale, Ben_HK
dc.contributor.authorToddBrown, Ken_HK
dc.contributor.authorThomas, Len_HK
dc.contributor.authorFerreira, MARen_HK
dc.contributor.authorBender, Den_HK
dc.contributor.authorMaller, Jen_HK
dc.contributor.authorSklar, Pen_HK
dc.contributor.authorDe Bakker, PIWen_HK
dc.contributor.authorDaly, MJen_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2010-09-06T08:19:14Z-
dc.date.available2010-09-06T08:19:14Z-
dc.date.issued2007en_HK
dc.identifier.citationAmerican Journal Of Human Genetics, 2007, v. 81 n. 3, p. 559-575en_HK
dc.identifier.issn0002-9297en_HK
dc.identifier.urihttp://hdl.handle.net/10722/81557-
dc.description.abstractWhole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis. © 2007 by The American Society of Human Genetics. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/en_HK
dc.relation.ispartofAmerican Journal of Human Geneticsen_HK
dc.rightsAmerican Journal of Human Genetics. Copyright © University of Chicago Press.en_HK
dc.titlePLINK: A tool set for whole-genome association and population-based linkage analysesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0002-9297&volume=81&spage=559&epage=575&date=2007&atitle=PLINK:+A+tool+set+for+whole-genome+association+and+population-based+linkage+analyses.en_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1086/519795en_HK
dc.identifier.pmid17701901en_HK
dc.identifier.scopuseid_2-s2.0-34548292504en_HK
dc.identifier.hkuros151791en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34548292504&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume81en_HK
dc.identifier.issue3en_HK
dc.identifier.spage559en_HK
dc.identifier.epage575en_HK
dc.identifier.eissn1537-6605-
dc.identifier.isiWOS:000249128200012-
dc.publisher.placeUnited Statesen_HK
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dc.identifier.scopusauthoridPurcell, S=7005489464en_HK
dc.identifier.scopusauthoridNeale, B=7003484514en_HK
dc.identifier.scopusauthoridToddBrown, K=20434773600en_HK
dc.identifier.scopusauthoridThomas, L=20434581800en_HK
dc.identifier.scopusauthoridFerreira, MAR=9740452100en_HK
dc.identifier.scopusauthoridBender, D=20337016100en_HK
dc.identifier.scopusauthoridMaller, J=14020129700en_HK
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dc.identifier.scopusauthoridDaly, MJ=7201456226en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.citeulike3292454-

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