Genome Wide Association Studies

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== Statistical Methodology ==
 
== Statistical Methodology ==
 +
 +
An important and widely used approach to dealing with cryptic population structure <cite>PricePC</cite>, and key references on genotype imputation <cite>ServinImputation</cite><cite>MarchiniImputation</cite>.
  
 
== Software ==
 
== Software ==
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More sophisticated model based genotype imputation and association testing can be performed using  
 
More sophisticated model based genotype imputation and association testing can be performed using  
 
[http://www.stats.ox.ac.uk/%7Emarchini/software/gwas/gwas.html IMPUTE and SNPTEST],
 
[http://www.stats.ox.ac.uk/%7Emarchini/software/gwas/gwas.html IMPUTE and SNPTEST],
or using
+
or  
 
[http://www.sph.umich.edu/csg/abecasis/mach MACH] and  
 
[http://www.sph.umich.edu/csg/abecasis/mach MACH] and  
[http://mga.bionet.nsc.ru/%7Eyurii/ABEL ProbABEL].
+
[http://mga.bionet.nsc.ru/%7Eyurii/ABEL ProbABEL], or [http://stephenslab.uchicago.edu/software.html BimBam].
  
 
Our own software for association testing using uncertain genotypes is
 
Our own software for association testing using uncertain genotypes is
 
[http://toby.freeshell.org/software/quicktest.shtml QUICKTEST].
 
[http://toby.freeshell.org/software/quicktest.shtml QUICKTEST].
 +
 +
== References ==
  
 
<biblio>
 
<biblio>
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# McCarthyReview pmid=18398418
 
# McCarthyReview pmid=18398418
 
# FlintReview pmid=15803197
 
# FlintReview pmid=15803197
 +
# PricePC pmid=16862161
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# ServinImputation pmid=17676998
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# MarchiniImputation pmid=17572673
 
</biblio>
 
</biblio>

Revision as of 16:19, 5 February 2009

Some people in our group work on genome wide association studies (GWAS).

Contents

Introductory reading

For an introduction to GWAS, with an emphasis on human studies, you could start with a nice tutorial article [1], and a review of more recent issues [2]. There is also a nice review about approaches for rodent studies [3].

Statistical Methodology

An important and widely used approach to dealing with cryptic population structure [4], and key references on genotype imputation [5][6].

Software

Many statistical methods are implemented in PLINK.

More sophisticated model based genotype imputation and association testing can be performed using IMPUTE and SNPTEST, or MACH and ProbABEL, or BimBam.

Our own software for association testing using uncertain genotypes is QUICKTEST.

References

  1. Balding DJ. A tutorial on statistical methods for population association studies. Nat Rev Genet 2006 Oct; 7(10) 781-91. doi:10.1038/nrg1916 pmid:16983374. PubMed HubMed [BaldingTutorial]
  2. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, and Hirschhorn JN. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet 2008 May; 9(5) 356-69. doi:10.1038/nrg2344 pmid:18398418. PubMed HubMed [McCarthyReview]
  3. Flint J, Valdar W, Shifman S, and Mott R. Strategies for mapping and cloning quantitative trait genes in rodents. Nat Rev Genet 2005 Apr; 6(4) 271-86. doi:10.1038/nrg1576 pmid:15803197. PubMed HubMed [FlintReview]
  4. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, and Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 2006 Aug; 38(8) 904-9. doi:10.1038/ng1847 pmid:16862161. PubMed HubMed [PricePC]
  5. Servin B and Stephens M. Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS Genet 2007 Jul; 3(7) e114. doi:10.1371/journal.pgen.0030114 pmid:17676998. PubMed HubMed [ServinImputation]
  6. Marchini J, Howie B, Myers S, McVean G, and Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 2007 Jul; 39(7) 906-13. doi:10.1038/ng2088 pmid:17572673. PubMed HubMed [MarchiniImputation]
All Medline abstracts: PubMed HubMed