Literature DB >> 18522673

Genetic association analysis: a primer on how it works, its strengths and its weaknesses.

Laura Rodriguez-Murillo1, David A Greenberg.   

Abstract

Currently, the most used approach to mapping disease genes is the genome wide association study, using large samples of cases and controls and hundreds of thousands of markers spread throughout the genome. This review focuses in explaining how an association study works, its strengths and its weaknesses, and the methods available to analyse the data. Issues related to sample size, genetic effect sizes, epistasis, replication and population stratification are specifically addressed, issues that an investigator must take into account when planning an association study of any complex disease. Finally, we include some special features concerning association studies in the Y chromosome, and we contrast the analysis characteristics of linkage and association.

Mesh:

Year:  2008        PMID: 18522673     DOI: 10.1111/j.1365-2605.2008.00896.x

Source DB:  PubMed          Journal:  Int J Androl        ISSN: 0105-6263


  8 in total

1.  AKT1 G205T genotype influences obesity-related metabolic phenotypes and their responses to aerobic exercise training in older Caucasians.

Authors:  Jennifer A McKenzie; Sarah Witkowski; Andrew T Ludlow; Stephen M Roth; James M Hagberg
Journal:  Exp Physiol       Date:  2010-11-19       Impact factor: 2.969

2.  SNP/haplotype associations in cytokine and cytokine receptor genes and immunity to rubella vaccine.

Authors:  Neelam Dhiman; Iana H Haralambieva; Richard B Kennedy; Robert A Vierkant; Megan M O'Byrne; Inna G Ovsyannikova; Robert M Jacobson; Gregory A Poland
Journal:  Immunogenetics       Date:  2010-03-10       Impact factor: 2.846

3.  Polymorphisms in the gene encoding bovine interleukin-10 receptor alpha are associated with Mycobacterium avium ssp. paratuberculosis infection status.

Authors:  Chris P Verschoor; Sameer D Pant; Qiumei You; Flavio S Schenkel; David F Kelton; Niel A Karrow
Journal:  BMC Genet       Date:  2010-04-15       Impact factor: 2.797

4.  Were genome-wide linkage studies a waste of time? Exploiting candidate regions within genome-wide association studies.

Authors:  Yun J Yoo; Shelley B Bull; Andrew D Paterson; Daryl Waggott; Lei Sun
Journal:  Genet Epidemiol       Date:  2010-02       Impact factor: 2.135

Review 5.  The impact of genetic research on our understanding of normal cognitive ageing: 1995 to 2009.

Authors:  Antony Payton
Journal:  Neuropsychol Rev       Date:  2009-09-19       Impact factor: 7.444

6.  Replication study of significant single nucleotide polymorphisms associated with myopia from two genome-wide association studies.

Authors:  Qin Wang; Yang Gao; Panfeng Wang; Shiqiang Li; Xiaoyun Jia; Xueshan Xiao; Xiangming Guo; Qingjiong Zhang
Journal:  Mol Vis       Date:  2011-12-16       Impact factor: 2.367

7.  Network-based SNP meta-analysis identifies joint and disjoint genetic features across common human diseases.

Authors:  Matthias Arnold; Mara L Hartsperger; Hansjörg Baurecht; Elke Rodríguez; Benedikt Wachinger; Andre Franke; Michael Kabesch; Juliane Winkelmann; Arne Pfeufer; Marcel Romanos; Thomas Illig; Hans-Werner Mewes; Volker Stümpflen; Stephan Weidinger
Journal:  BMC Genomics       Date:  2012-09-18       Impact factor: 3.969

8.  Using linkage analysis to detect gene-gene interaction by stratifying family data on known disease, or disease-associated, alleles.

Authors:  Barbara Corso; David A Greenberg
Journal:  PLoS One       Date:  2014-04-01       Impact factor: 3.240

  8 in total

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