Literature DB >> 25599666

Statistical methods for genome-wide and sequencing association studies of complex traits in related samples.

Timothy A Thornton1.   

Abstract

Genome-wide association studies (GWAS) and sequencing studies are routinely conducted for the identification of genetic variants that are associated with complex traits. Many genetic studies for association mapping include related individuals. When relatives are included in an association analysis, familial correlations must be appropriately taken into account to ensure correct type I error and to increase power. This unit provides an overview of statistical methods that are available for GWAS and sequencing association studies of complex traits in samples with related individuals.
Copyright © 2015 John Wiley & Sons, Inc.

Entities:  

Keywords:  GWAS; association mapping; complex traits; family data; genome-wide association studies; mixed models; relatedness; sequence

Mesh：

Year:  2015        PMID： 25599666      PMCID： PMC4327940          DOI： 10.1002/0471142905.hg0128s84

Source DB:  PubMed          Journal:  Curr Protoc Hum Genet        ISSN： 1934-8258


  36 in total

1.  A general test of association for quantitative traits in nuclear families.

Authors:  G R Abecasis; L R Cardon; W O Cookson
Journal:  Am J Hum Genet       Date:  2000-01       Impact factor: 11.025

2.  Quantitative-trait homozygosity and association mapping and empirical genomewide significance in large, complex pedigrees: fasting serum-insulin level in the Hutterites.

Authors:  Mark Abney; Carole Ober; Mary Sara McPeek
Journal:  Am J Hum Genet       Date:  2002-03-04       Impact factor: 11.025

3.  Methods for detecting and correcting for population stratification.

Authors:  Todd L Edwards; Xiaoyi Gao
Journal:  Curr Protoc Hum Genet       Date:  2012-04

4.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

Review 5.  Next-generation DNA sequencing methods.

Authors:  Elaine R Mardis
Journal:  Annu Rev Genomics Hum Genet       Date:  2008       Impact factor: 8.929

6.  Multiple genetic variant association testing by collapsing and kernel methods with pedigree or population structured data.

Authors:  Daniel J Schaid; Shannon K McDonnell; Jason P Sinnwell; Stephen N Thibodeau
Journal:  Genet Epidemiol       Date:  2013-05-05       Impact factor: 2.135

7.  Rapid variance components-based method for whole-genome association analysis.

Authors:  Gulnara R Svishcheva; Tatiana I Axenovich; Nadezhda M Belonogova; Cornelia M van Duijn; Yurii S Aulchenko
Journal:  Nat Genet       Date:  2012-09-16       Impact factor: 38.330

8.  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

9.  The relative power of family-based and case-control designs for linkage disequilibrium studies of complex human diseases. II. Individual genotyping.

Authors:  J Teng; N Risch
Journal:  Genome Res       Date:  1999-03       Impact factor: 9.043

10.  Advantages and pitfalls in the application of mixed-model association methods.

Authors:  Jian Yang; Noah A Zaitlen; Michael E Goddard; Peter M Visscher; Alkes L Price
Journal:  Nat Genet       Date:  2014-02       Impact factor: 38.330
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  1 in total

1.  Association of genetic polymorphisms related to Johne's disease with estimated breeding values of Holstein sires for milk ELISA test scores.

Authors:  Sanjay Mallikarjunappa; Flavio S Schenkel; Luiz F Brito; Nathalie Bissonnette; Filippo Miglior; Jacques Chesnais; Michael Lohuis; Kieran G Meade; Niel A Karrow
Journal:  BMC Vet Res       Date:  2020-05-27       Impact factor: 2.741
  1 in total

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