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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A genome-wide investigation of SNPs and CNVs in schizophrenia
Anna C. Need,Dongliang Ge,Michael E. Weale,Jessica M. Maia,Sheng Feng,Erin L. Heinzen,Kevin V. Shianna,Woohyun Yoon,Dalia Kasperavičiūtė,Massimo Gennarelli,Warren J. Strittmatter,Cristian Bonvicini,Giuseppe Rossi,Karu Jayathilake,Philip A. Cola,Joseph P. McEvoy,Richard S.E. Keefe,Elizabeth M. C. Fisher,Pamela L. St. Jean,Ina Giegling,Annette M. Hartmann,Hans-Jürgen Möller,Andreas Ruppert,Gillian Fraser,Caroline Crombie,Lefkos T. Middleton,David St Clair,Allen D. Roses,Pierandrea Muglia,Clyde Francks,Dan Rujescu,Herbert Y. Meltzer,David Goldstein +32 more
TL;DR: These data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms.
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α-5/α-3 nicotinic receptor subunit alleles increase risk for heavy smoking
Wade H. Berrettini,Wade H. Berrettini,Xin Yuan,Federica Tozzi,Kijoung Song,Clyde Francks,H. D. Chilcoat,Dawn M. Waterworth,Pierandrea Muglia,Pierandrea Muglia,Vincent Mooser +10 more
TL;DR: It is suggested that a common haplotype in the CHRNA5/CHRNA3 gene cluster on chromosome 15 contains alleles, which predispose to ND, which are assessed in three independent populations of European origin.
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Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia.
Johan Rung,Stéphane Cauchi,Anders Albrechtsen,Lishuang Shen,Lishuang Shen,Ghislain Rocheleau,Ghislain Rocheleau,Christine Cavalcanti-Proença,Francois Bacot,Beverley Balkau,Alexandre Belisle,Knut Borch-Johnsen,Guillaume Charpentier,Christian Dina,Emmanuelle Durand,Paul Elliott,Samy Hadjadj,Marjo-Riitta Järvelin,Marjo-Riitta Järvelin,Jaana Laitinen,Torsten Lauritzen,Michel Marre,Alexander Mazur,David Meyre,Alexandre Montpetit,Charlotta Pisinger,Barry I. Posner,Pernille Poulsen,Anneli Pouta,Anneli Pouta,Marc Prentki,Rasmus Ribel-Madsen,Aimo Ruokonen,A. Sandbaek,David Serre,David Serre,Jean Tichet,Martine Vaxillaire,Jørgen F. P. Wojtaszewski,Allan Vaag,Allan Vaag,Torben Hansen,Torben Hansen,Constantin Polychronakos,Oluf Pedersen,Oluf Pedersen,Philippe Froguel,Philippe Froguel,Robert Sladek +48 more
TL;DR: The C allele of rs2943641 was associated with insulin resistance and hyperinsulinemia in 14,358 French, Danish and Finnish participants from population-based cohorts; this allele was also associated with reduced basal levels of IRS1 protein and decreased insulin induction of IRS 1-associated phosphatidylinositol-3-OH kinase activity in human skeletal muscle biopsies.
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ProbABEL package for genome-wide association analysis of imputed data
TL;DR: The ProbABEL software package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci.
Ancient human genomes suggest three ancestral populations for present-day Europeans
Iosif Lazaridis,Iosif Lazaridis,Nick Patterson,Alissa Mittnik,Gabriel Renaud,Swapan Mallick,Swapan Mallick,Karola Kirsanow,Peter H. Sudmant,Joshua G. Schraiber,Joshua G. Schraiber,Sergi Castellano,Mark Lipson,Bonnie Berger,Bonnie Berger,Christos Economou,Ruth Bollongino,Qiaomei Fu,Kirsten I. Bos,Susanne Nordenfelt,Susanne Nordenfelt,Heng Li,Heng Li,Cesare de Filippo,Kay Prüfer,Susanna Sawyer,Cosimo Posth,Wolfgang Haak,Fredrik Hallgren,Elin Fornander,Nadin Rohland,Nadin Rohland,Dominique Delsate,Michael Francken,Jean-Michel Guinet,Joachim Wahl,George Ayodo,Hamza A. Babiker,Hamza A. Babiker,Graciela Bailliet,Elena Balanovska,Oleg Balanovsky,Ramiro Barrantes,Gabriel Bedoya,Haim Ben-Ami,Judit Bene,Fouad Berrada,Claudio M. Bravi,Francesca Brisighelli,George B.J. Busby,Francesco Calì,Mikhail Churnosov,David E. C. Cole,Daniel Corach,Larissa Damba,George van Driem,Stanislav Dryomov,Jean-Michel Dugoujon,Sardana A. Fedorova,Irene Gallego Romero,Marina Gubina,Michael F. Hammer,Brenna M. Henn,Tor Hervig,Ugur Hodoglugil,Aashish R. Jha,Sena Karachanak-Yankova,Rita Khusainova,Elza Khusnutdinova,Rick A. Kittles,Toomas Kivisild,William Klitz,Vaidutis Kučinskas,Alena Kushniarevich,Leila Laredj,Sergey Litvinov,Theologos Loukidis,Theologos Loukidis,Robert W. Mahley,Béla Melegh,Ene Metspalu,Julio Molina,Joanna L. Mountain,Klemetti Näkkäläjärvi,Desislava Nesheva,Thomas B. Nyambo,Ludmila P. Osipova,Jüri Parik,Fedor Platonov,Olga L. Posukh,Valentino Romano,Francisco Rothhammer,Francisco Rothhammer,Igor Rudan,Ruslan Ruizbakiev,Hovhannes Sahakyan,Hovhannes Sahakyan,Antti Sajantila,Antonio Salas,Elena B. Starikovskaya,Ayele Tarekegn,Draga Toncheva,Shahlo Turdikulova,Ingrida Uktveryte,Olga Utevska,René Vasquez,Mercedes Villena,Mikhail Voevoda,Cheryl A. Winkler,Levon Yepiskoposyan,Pierre Zalloua,Pierre Zalloua,Tatijana Zemunik,Alan Cooper,Cristian Capelli,Mark G. Thomas,Andres Ruiz-Linares,Sarah A. Tishkoff,Lalji Singh,Kumarasamy Thangaraj,Richard Villems,Richard Villems,Richard Villems,David Comas,Rem I. Sukernik,Mait Metspalu,Matthias Meyer,Evan E. Eichler,Joachim Burger,Montgomery Slatkin,Svante Pääbo,Janet Kelso,David Reich,David Reich,David Reich,Johannes Krause,Johannes Krause +136 more
TL;DR: The authors showed that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunters-gatherer related ancestry.
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