Movatterモバイル変換

[0]ホーム
URL:

Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
Thehttps:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

NIH NLM Logo
Log inShow account info
Access keysNCBI HomepageMyNCBI HomepageMain ContentMain Navigation
pubmed logo
Advanced Clipboard
User Guide

Full text links

Elsevier Science full text link Elsevier Science Free PMC article
Full text links

Actions

Share

.2007 Sep;81(3):559-75.
doi: 10.1086/519795. Epub 2007 Jul 25.

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

Affiliations

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

Shaun Purcell et al. Am J Hum Genet.2007 Sep.

Abstract

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.

PubMed Disclaimer

Figures

Figure A1.
Figure A1.
Example transmissions and corresponding IBD states. For two haploid genomes,C1 andC2, the figure illustrates four (of many) possible patterns of transmission and the corresponding IBD states at two positions,U andV. The text describes how consideration of these possible scenarios leads to the specification of transition matrices for IBD state along the chromosome.
Figure 1.
Figure 1.
MDS and classification of Asian HapMap individuals. MDS reveals in each panel two clear clusters that correspond to CHB (left) and JPT (right) HapMap populations. The figure’s three panels differ only in the color scheme, which represents classification according to PPC thresholds of 0.01 (A), 0.001 (B), and 0.0001 (C).
Figure 2.
Figure 2.
Example segment shared IBD between two HapMap CEU offspring individuals and their parents. The main set of plots show the multipoint estimate of IBD sharing,P(Z=1), for a 25-Mb region of chromosome 9, for the pairs of individuals between two families (CEPH1375 and CEPH1341). The region was selected because the two offspring (NA10863 and NA06991) showed sharing in this region, shown in plot a. The three other segments shared between seemingly unrelated individuals are shown—that is, between the offspring in one family and a parent in the other family (two plots labeled b and c) and between those two parents (plot d). The lower-left diagram illustrates the region shared; this extended haplotype spans multiple haplotype blocks and recombination hotspots in the full phase II data. The lower-right diagram depicts the pattern of gene flow for this particular region—that is, a segment of the original common chromosome (dark rectangles) appears in the two families as shown.
Figure 3.
Figure 3.
Schema of integration of PLINK, gPLINK, and Haploview. PLINK is the main C/C++ WGAS analytic engine that can run either as a stand-alone tool (from the command line or via shell scripting) or in conjunction with gPLINK, a Java-based graphical user interface (GUI). gPLINK also offers a simple project management framework to track PLINK analyses and facilitates integration with Haploview. It is easy to configure these tools, such that the whole-genome data and PLINK analyses (i.e., the computationally expensive aspects of this process) can reside on a remote server, but all initiation and viewing of results is done locally—for example, on a user’s laptop, connected to the whole-genome data via the Internet, by use of gPLINK’s secure shell networking.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

Web Resources

    1. Haploview,http://www.broad.mit.edu/mpg/haploview/
    1. HapMap,http://www.hapmap.org/
    1. PLINK and gPLINK,http://pngu.mgh.harvard.edu/purcell/plink/
    1. Queue portal at the Coriell Institute,https://queue.coriell.org/q/

References

    1. Lander ES, Schork NJ (1994) Genetic dissection of complex traits. Science 265:2037–2048 (erratum 266:353)10.1126/science.8091226 - DOI - PubMed
    1. Risch N, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273:1516–151710.1126/science.273.5281.1516 - DOI - PubMed
    1. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K (2002) A comprehensive review of genetic association studies. Genet Med 4:45–61 - PubMed
    1. Ioannidis JP, Trikalinos TA, Khoury MJ (2006) Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases. Am J Epidemiol 164:609–61410.1093/aje/kwj259 - DOI - PubMed
    1. Reich DE, Lander ES (2001) On the allelic spectrum of human disease. Trends Genet 17:502–51010.1016/S0168-9525(01)02410-6 - DOI - PubMed

Publication types

MeSH terms

Related information

Grants and funding

LinkOut - more resources

Full text links
Elsevier Science full text link Elsevier Science Free PMC article
Cite
Send To

NCBI Literature Resources

MeSHPMCBookshelfDisclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

[8]ページ先頭
©2009-2025 Movatter.jp