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Article: PLINK: A tool set for whole-genome association and population-based linkage analyses
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TitlePLINK: A tool set for whole-genome association and population-based linkage analyses
 
AuthorsPurcell, S2 4
Neale, B1 4
ToddBrown, K
Thomas, L
Ferreira, MAR
Bender, D4
Maller, J4
Sklar, P4
De Bakker, PIW4
Daly, MJ4
Sham, PC3
 
Issue Date2007
 
PublisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
 
CitationAmerican Journal Of Human Genetics, 2007, v. 81 n. 3, p. 559-575 [How to Cite?]
DOI: http://dx.doi.org/10.1086/519795
 
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.
 
ISSN0002-9297
2013 Impact Factor: 10.987
 
DOIhttp://dx.doi.org/10.1086/519795
 
ISI Accession Number IDWOS:000249128200012
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorPurcell, S
 
dc.contributor.authorNeale, B
 
dc.contributor.authorToddBrown, K
 
dc.contributor.authorThomas, L
 
dc.contributor.authorFerreira, MAR
 
dc.contributor.authorBender, D
 
dc.contributor.authorMaller, J
 
dc.contributor.authorSklar, P
 
dc.contributor.authorDe Bakker, PIW
 
dc.contributor.authorDaly, MJ
 
dc.contributor.authorSham, PC
 
dc.date.accessioned2010-09-06T08:19:14Z
 
dc.date.available2010-09-06T08:19:14Z
 
dc.date.issued2007
 
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.
 
dc.description.naturelink_to_subscribed_fulltext
 
dc.identifier.citationAmerican Journal Of Human Genetics, 2007, v. 81 n. 3, p. 559-575 [How to Cite?]
DOI: http://dx.doi.org/10.1086/519795
 
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dc.languageeng
 
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
 
dc.publisher.placeUnited States
 
dc.relation.ispartofAmerican Journal of Human Genetics
 
dc.relation.referencesReferences in Scopus
 
dc.rightsAmerican Journal of Human Genetics. Copyright © University of Chicago Press.
 
dc.titlePLINK: A tool set for whole-genome association and population-based linkage analyses
 
dc.typeArticle
 
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Author Affiliations
  1. King's College London
  2. Massachusetts General Hospital
  3. The University of Hong Kong
  4. Broad Institute