Difference between revisions of "Genome Wide Association Studies"
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# ServinImputation pmid=17676998 | # ServinImputation pmid=17676998 | ||
# MarchiniImputation pmid=17572673 | # MarchiniImputation pmid=17572673 | ||
| − | # | + | # KangEMMA pmid=18385116 |
</biblio> | </biblio> | ||
Revision as of 15:29, 5 February 2009
Some people in our group work on genome wide association studies (GWAS).
Introductory reading
For an introduction to GWAS, with an emphasis on human studies, you could start with a nice tutorial article BaldingTutorial, and a review of more recent issues McCarthyReview. There is also a nice review about approaches for rodent studies FlintReview.
Statistical Methodology
An important and widely used approach to dealing with cryptic population structure PricePC, and key references on genotype imputation ServinImputationMarchiniImputation.
A powerful approach to deal with strain structure or relatedness between individuals KangEMMA.
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
<biblio>
- BaldingTutorial pmid=16983374
- McCarthyReview pmid=18398418
- FlintReview pmid=15803197
- PricePC pmid=16862161
- ServinImputation pmid=17676998
- MarchiniImputation pmid=17572673
- KangEMMA pmid=18385116
</biblio>
