Copyright © 2005 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 76, Issue 5, 773-779, 1 May 2005
doi:10.1086/429843
Adrian Vella1, Jason D. Cooper1, Christopher E. Lowe1, Neil Walker1, Sarah Nutland1, Barry Widmer2, Richard Jones3, Susan M. Ring3, Wendy McArdle3, Marcus E. Pembrey3, 4, David P. Strachan5, David B. Dunger2, C.J. Rebecca Twells1, David G. Clayton1 and John A. Todd1,
, 
1 Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, United Kingdom
2 Department of Paediatrics, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
3 Department of Community-Based Medicine, Bristol University, Bristol, United Kingdom
4 Clinical and Molecular Genetics Unit, Institute of Child Health, University College London, London
5 Department of Community Health Sciences, St. George’s Hospital Medical School, London
Address for correspondence and reprints: Prof. John A. Todd, Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, University of Cambridge, Cambridge Institute for Medical Research, Wellcome Trust/Medical Research Council Building, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 2XY, United KingdomAbstract
As part of an ongoing search for genes associated with type 1 diabetes (T1D), a common autoimmune disease, we tested the biological candidate gene IL2RA (CD25), which encodes a subunit (IL-2Rα) of the high-affinity interleukin-2 (IL-2) receptor complex. We employed a tag single-nucleotide polymorphism (tag SNP) approach in large T1D sample collections consisting of 7,457 cases and controls and 725 multiplex families. Tag SNPs were analyzed using a multilocus test to provide a regional test for association. We found strong statistical evidence in the case-control collection (P=6.5×10−8) for a T1D locus in the CD25 region of chromosome 10p15 and replicated the association in the family collection (P=7.3×10−3; combined P=1.3×10−10). These results illustrate the utility of tag SNPs in a chromosome-regional test of disease association and justify future fine mapping of the causal variant in the region.
| Rapid Simulation of P Values for Product Methods and Multiple-Testing Adjustment in Association Studies The American Journal of Human Genetics, Volume 76, Issue 3, 1 March 2005, Pages 399-408 S.R. Seaman and B. Müller-Myhsok Abstract A major aim of association studies is the identification of polymorphisms (usually SNPs) associated with a trait. Tests of association may be based on individual SNPs or on sets of neighboring SNPs, by use of (for example) a product P value method or Hotelling's T test. Linkage disequilibrium, the nonindependence of SNPs in physical proximity, causes problems for all these tests. First, multiple-testing correction for individual-SNP tests or for multilocus tests either leads to conservative P values (if Bonferroni correction is used) or is computationally expensive (if permutation is used). Second, calculation of product P values usually requires permutation. Here, we present the direct simulation approach (DSA), a method that accurately approximates P values obtained by permutation but is much faster. It may be used whenever tests are based on score statistics—for example, with Armitage's trend test or its multivariate analogue. The DSA can be used with binary, continuous, or count traits and allows adjustment for covariates. We demonstrate the accuracy of the DSA on real and simulated data and illustrate how it might be used in the analysis of a whole-genome association study. Abstract | | |
| A Fast and Flexible Statistical Model for Large-Scale Population Genotype Data: Applications to Inferring Missing Genotypes and Haplotypic Phase The American Journal of Human Genetics, Volume 78, Issue 4, 1 April 2006, Pages 629-644 Paul Scheet and Matthew Stephens Abstract We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both “block-like” patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide–polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site. Abstract | | |