Bayesian refinement of association signals for 14 loci in 3 common diseases

@article{Maller2012BayesianRO,
  title={Bayesian refinement of association signals for 14 loci in 3 common diseases},
  author={Julian B. Maller and Gilean McVean and Jake K. Byrnes and Damjan Vukcevic and Kimmo Palin and Zhan Su and Joanna M. M. Howson and Adam Auton and Simon Richard Myers and Andrew P. Morris and Matti Pirinen and Matthew A Brown and Paul R. Burton and Mark J. Caulfield and Alastair D Compston and Martin Farrall and Alistair Scott Hall and Andrew T Hattersley and Adrian V S Hill and Christopher G Mathew and Marcus Pembrey and Jack Satsangi and Michael R. Stratton and Jane Worthington and Nick J. Craddock and Matthew E. Hurles and Willem H Ouwehand and M. B. A. Parkes and Nazneen Rahman and Audrey Duncanson and John A. Todd and Dominic P Kwiatkowski and Nilesh J. Samani and Stephen C. L. Gough and Mark I. McCarthy and Panagiotis Deloukas and Peter Donnelly},
  journal={Nature Genetics},
  year={2012},
  volume={44},
  pages={1294-1301}
}
To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on… CONTINUE READING