PLINK: a tool set for whole-genome association and population-based linkage analyses.
Whole-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.
Purcell
Shaun
S
Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA. shaun@pngu.mgh.harvard.edu
Neale
Benjamin
B
Todd-Brown
Kathe
K
Thomas
Lori
L
Ferreira
Manuel A R
MA
Bender
David
D
Maller
Julian
J
Sklar
Pamela
P
de Bakker
Paul I W
PI
Daly
Mark J
MJ
Sham
Pak C
PC
D008040:Genetic Linkage / Q000235:genetics*; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D011153:Population / Q000235:genetics*; D012984:Software
Am J Hum Genet. 1995 Aug;57(2):455-64
7668272
Proc Natl Acad Sci U S A. 2004 Aug 10;101(32):11689-94
15273283
Science. 2005 Oct 14;310(5746):321-4
16224025
Proc Natl Acad Sci U S A. 1987 Apr;84(8):2363-7
3470801
Hum Hered. 2005;59(2):67-78
15838176
Am J Epidemiol. 2006 Oct 1;164(7):609-14
16893921
Science. 1994 Sep 30;265(5181):2037-48
8091226
Int J Epidemiol. 2003 Dec;32(6):1120
14681291
Am J Hum Genet. 1999 Jan;64(1):259-67
9915965
Am J Hum Genet. 2001 Jul;69(1):124-37
11404818
Biometrics. 1999 Dec;55(4):997-1004
11315092
Genetics. 2003 Mar;163(3):1153-67
12663552
Nat Genet. 2005 Nov;37(11):1243-6
16228001
Am J Hum Genet. 2005 Feb;76(2):249-59
15614722
Am J Hum Genet. 1998 Feb;62(2):450-8
9463321
Am J Hum Genet. 2006 Apr;78(4):615-28
16532392
Genet Med. 2002 Mar-Apr;4(2):45-61
11882781
Trends Genet. 2001 Sep;17(9):502-10
11525833
Hum Hered. 2004;58(2):93-107
15711089
Nat Genet. 2004 Apr;36(4):388-93
15052270
Genetics. 1994 Nov;138(3):963-71
7851788
Nat Genet. 2006 Jun;38(6):663-7
16715096
Science. 1996 Sep 13;273(5281):1516-7
8801636
Science. 2007 Jun 1;316(5829):1331-6
17463246
Behav Genet. 2007 Jul;37(4):631-6
17372818
Clin Exp Allergy. 1995 Nov;25 Suppl 2:97-102
8590355
Am J Hum Genet. 2005 May;76(5):887-93
15789306
Nat Genet. 1994 Dec;8(4):380-6
7894490
Nat Rev Genet. 2005 Feb;6(2):95-108
15716906
Bioinformatics. 2005 Jan 15;21(2):263-5
15297300
Am J Hum Genet. 1999 Dec;65(6):1493-500
10577902
Nat Genet. 2006 Aug;38(8):904-9
16862161
Am J Hum Genet. 2000 Jan;66(1):279-92
10631157
Genome Res. 2001 Dec;11(12):2115-9
11731502
Genetics. 2000 Jun;155(2):945-59
10835412