Literature DB >> 19913122

ATRIUM: testing untyped SNPs in case-control association studies with related individuals.

Zuoheng Wang1, Mary Sara McPeek.   

Abstract

In genome-wide association studies, only a subset of all genomic variants are typed by current, high-throughput, SNP-genotyping platforms. However, many of the untyped variants can be well predicted from typed variants, with linkage disequilibrium (LD) information among typed and untyped variants available from an external reference panel such as HapMap. Incorporation of such external information can allow one to perform tests of association between untyped variants and phenotype, thereby making more efficient use of the available genotype data. When related individuals are included in case-control samples, the dependence among their genotypes must be properly addressed for valid association testing. In the context of testing untyped variants, an additional analytical challenge is that the dependence, across related individuals, of the partial information on untyped-SNP genotypes must also be assessed and incorporated into the analysis for valid inference. We address this challenge with ATRIUM, a method for case-control association testing with untyped SNPs, based on genome screen data in samples in which some individuals are related. ATRIUM uses LD information from an external reference panel to specify a one-degree-of-freedom test of association with an untyped SNP. It properly accounts for dependence in the partial information on untyped-SNP genotypes across related individuals. We demonstrate that ATRIUM is robust in that it maintains the nominal type I error rate even when the external reference panel is not well matched to the case-control sample. We apply the method to detect association between type 2 diabetes and variants on chromosome 10 in the Framingham SHARe data.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19913122      PMCID: PMC2775837          DOI: 10.1016/j.ajhg.2009.10.006

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  35 in total

1.  Efficiency and power in genetic association studies.

Authors:  Paul I W de Bakker; Roman Yelensky; Itsik Pe'er; Stacey B Gabriel; Mark J Daly; David Altshuler
Journal:  Nat Genet       Date:  2005-10-23       Impact factor: 38.330

2.  Multilocus linkage disequilibrium mapping by the decay of haplotype sharing with samples of related individuals.

Authors:  Jian Zhang; Daniel Schneider; Carole Ober; Mary Sara McPeek
Journal:  Genet Epidemiol       Date:  2005-09       Impact factor: 2.135

3.  A new multipoint method for genome-wide association studies by imputation of genotypes.

Authors:  Jonathan Marchini; Bryan Howie; Simon Myers; Gil McVean; Peter Donnelly
Journal:  Nat Genet       Date:  2007-06-17       Impact factor: 38.330

4.  Simple and efficient analysis of disease association with missing genotype data.

Authors:  D Y Lin; Y Hu; B E Huang
Journal:  Am J Hum Genet       Date:  2008-02       Impact factor: 11.025

5.  The Third Generation Cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: design, recruitment, and initial examination.

Authors:  Greta Lee Splansky; Diane Corey; Qiong Yang; Larry D Atwood; L Adrienne Cupples; Emelia J Benjamin; Ralph B D'Agostino; Caroline S Fox; Martin G Larson; Joanne M Murabito; Christopher J O'Donnell; Ramachandran S Vasan; Philip A Wolf; Daniel Levy
Journal:  Am J Epidemiol       Date:  2007-03-19       Impact factor: 4.897

6.  An Incomplete-Data Quasi-likelihood Approach to Haplotype-Based Genetic Association Studies on Related Individuals.

Authors:  Zuoheng Wang; Mary Sara McPeek
Journal:  J Am Stat Assoc       Date:  2009-09-01       Impact factor: 5.033

7.  Genetic analysis of non-insulin dependent diabetes mellitus in the GK rat.

Authors:  J Galli; L S Li; A Glaser; C G Ostenson; H Jiao; H Fakhrai-Rad; H J Jacob; E S Lander; H Luthman
Journal:  Nat Genet       Date:  1996-01       Impact factor: 38.330

8.  Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels.

Authors:  Richa Saxena; Benjamin F Voight; Valeriya Lyssenko; Noël P Burtt; Paul I W de Bakker; Hong Chen; Jeffrey J Roix; Sekar Kathiresan; Joel N Hirschhorn; Mark J Daly; Thomas E Hughes; Leif Groop; David Altshuler; Peter Almgren; Jose C Florez; Joanne Meyer; Kristin Ardlie; Kristina Bengtsson Boström; Bo Isomaa; Guillaume Lettre; Ulf Lindblad; Helen N Lyon; Olle Melander; Christopher Newton-Cheh; Peter Nilsson; Marju Orho-Melander; Lennart Råstam; Elizabeth K Speliotes; Marja-Riitta Taskinen; Tiinamaija Tuomi; Candace Guiducci; Anna Berglund; Joyce Carlson; Lauren Gianniny; Rachel Hackett; Liselotte Hall; Johan Holmkvist; Esa Laurila; Marketa Sjögren; Maria Sterner; Aarti Surti; Margareta Svensson; Malin Svensson; Ryan Tewhey; Brendan Blumenstiel; Melissa Parkin; Matthew Defelice; Rachel Barry; Wendy Brodeur; Jody Camarata; Nancy Chia; Mary Fava; John Gibbons; Bob Handsaker; Claire Healy; Kieu Nguyen; Casey Gates; Carrie Sougnez; Diane Gage; Marcia Nizzari; Stacey B Gabriel; Gung-Wei Chirn; Qicheng Ma; Hemang Parikh; Delwood Richardson; Darrell Ricke; Shaun Purcell
Journal:  Science       Date:  2007-04-26       Impact factor: 47.728

9.  Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes.

Authors:  Eleftheria Zeggini; Michael N Weedon; Cecilia M Lindgren; Timothy M Frayling; Katherine S Elliott; Hana Lango; Nicholas J Timpson; John R B Perry; Nigel W Rayner; Rachel M Freathy; Jeffrey C Barrett; Beverley Shields; Andrew P Morris; Sian Ellard; Christopher J Groves; Lorna W Harries; Jonathan L Marchini; Katharine R Owen; Beatrice Knight; Lon R Cardon; Mark Walker; Graham A Hitman; Andrew D Morris; Alex S F Doney; Mark I McCarthy; Andrew T Hattersley
Journal:  Science       Date:  2007-04-26       Impact factor: 47.728

10.  Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

Authors:  Cristen J Willer; Serena Sanna; Anne U Jackson; Angelo Scuteri; Lori L Bonnycastle; Robert Clarke; Simon C Heath; Nicholas J Timpson; Samer S Najjar; Heather M Stringham; James Strait; William L Duren; Andrea Maschio; Fabio Busonero; Antonella Mulas; Giuseppe Albai; Amy J Swift; Mario A Morken; Narisu Narisu; Derrick Bennett; Sarah Parish; Haiqing Shen; Pilar Galan; Pierre Meneton; Serge Hercberg; Diana Zelenika; Wei-Min Chen; Yun Li; Laura J Scott; Paul A Scheet; Jouko Sundvall; Richard M Watanabe; Ramaiah Nagaraja; Shah Ebrahim; Debbie A Lawlor; Yoav Ben-Shlomo; George Davey-Smith; Alan R Shuldiner; Rory Collins; Richard N Bergman; Manuela Uda; Jaakko Tuomilehto; Antonio Cao; Francis S Collins; Edward Lakatta; G Mark Lathrop; Michael Boehnke; David Schlessinger; Karen L Mohlke; Gonçalo R Abecasis
Journal:  Nat Genet       Date:  2008-01-13       Impact factor: 38.330

View more
  5 in total

1.  Generalized functional linear models for gene-based case-control association studies.

Authors:  Ruzong Fan; Yifan Wang; James L Mills; Tonia C Carter; Iryna Lobach; Alexander F Wilson; Joan E Bailey-Wilson; Daniel E Weeks; Momiao Xiong
Journal:  Genet Epidemiol       Date:  2014-09-09       Impact factor: 2.135

2.  Development of GMDR-GPU for gene-gene interaction analysis and its application to WTCCC GWAS data for type 2 diabetes.

Authors:  Zhixiang Zhu; Xiaoran Tong; Zhihong Zhu; Meimei Liang; Wenyan Cui; Kunkai Su; Ming D Li; Jun Zhu
Journal:  PLoS One       Date:  2013-04-23       Impact factor: 3.240

3.  Association analysis of complex diseases using triads, parent-child dyads and singleton monads.

Authors:  Ruzong Fan; Annie Lee; Zhaohui Lu; Aiyi Liu; James F Troendle; James L Mills
Journal:  BMC Genet       Date:  2013-09-04       Impact factor: 2.797

4.  Mega2: validated data-reformatting for linkage and association analyses.

Authors:  Robert V Baron; Charles Kollar; Nandita Mukhopadhyay; Daniel E Weeks
Journal:  Source Code Biol Med       Date:  2014-12-05

5.  CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates.

Authors:  Sheng Zhong; Duo Jiang; Mary Sara McPeek
Journal:  PLoS Genet       Date:  2016-10-03       Impact factor: 5.917

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.