PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses
Shaun Purcell,Shaun Purcell,Benjamin M. Neale,Benjamin M. Neale,Kathe Todd-Brown,Lori Thomas,Manuel A. R. Ferreira,David Bender,David Bender,Julian Maller,Julian Maller,Pamela Sklar,Pamela Sklar,Paul I.W. de Bakker,Paul I.W. de Bakker,Mark J. Daly,Mark J. Daly,Pak C. Sham +17 more
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TLDR
This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.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.read more
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Genome-wide association study of recurrent early-onset major depressive disorder.
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Common Missense Variant in the Glucokinase Regulatory Protein Gene Is Associated With Increased Plasma Triglyceride and C-Reactive Protein but Lower Fasting Glucose Concentrations
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Ancient Ethiopian genome reveals extensive Eurasian admixture throughout the African continent
M. Gallego Llorente,Eppie R. Jones,Anders Eriksson,Anders Eriksson,Veronika Siska,Kathryn Weedman Arthur,John W. Arthur,Matthew C. Curtis,Matthew C. Curtis,Jay T. Stock,Mauro Coltorti,Pierluigi Pieruccini,Sean Stretton,Fiona Brock,Fiona Brock,Thomas Higham,Y.-K. Park,Michael Hofreiter,Michael Hofreiter,Daniel G. Bradley,Jong Bhak,Ron Pinhasi,Andrea Manica +22 more
TL;DR: The genome of an Ethiopian male, “Mota,” who lived approximately 4500 years ago is sequenced to demonstrate that the Eurasian backflow into Africa came from a population closely related to Early Neolithic farmers, who had colonized Europe 4000 years earlier.
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