Copyright © 1999 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 65, Issue 4, 1170-1177, 1 October 1999
doi:10.1086/302577
MRC Biostatistics Unit, Institute of Public Health, Cambridge
Address for correspondence and reprints: Dr. David Clayton, MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, United KingdomAbstract
A new transmission/disequilibrium-test statistic is proposed for situations in which transmission is uncertain. Such situations arise when transmission of a multilocus marker haplotype is considered, since haplotype phase is often unknown in a substantial number of instances. Even for single-locus markers, transmission is uncertain if one or both parents are missing. In both these situations, uncertainty may be reduced by the typing of further siblings, whose disease status may be unaffected or unknown. The proposed test is a score test based on a partial score function that omits the terms most influenced by hidden population stratification.
| Transmission/Disequilibrium Test Meets Measured Haplotype Analysis: Family-Based Association Analysis Guided by Evolution of Haplotypes The American Journal of Human Genetics, Volume 68, Issue 5, 1 May 2001, Pages 1250-1263 Howard Seltman, Kathryn Roeder and B. Devlin Abstract Family data teamed with the transmission/disequilibrium test (TDT), which simultaneously evaluates linkage and association, is a powerful means of detecting disease-liability alleles. To increase the information provided by the test, various researchers have proposed TDT-based methods for haplotype transmission. Haplotypes indeed produce more-definitive transmissions than do the alleles comprising them, and this tends to increase power. However, the larger number of haplotypes, relative to alleles at individual loci, tends to decrease power, because of the additional degrees of freedom required for the test. An optimal strategy would focus the test on particular haplotypes or groups of haplotypes. In this report we develop such an approach by combining the theory of TDT with that of measured haplotype analysis (MHA). MHA uses the evolutionary relationships among haplotypes to produce a limited set of hypothesis tests and to increase the interpretability of these tests. The theory of our approach, called the “evolutionary tree” (ET)–TDT, is developed for two cases: when haplotype transmission is certain and when it is not. Simulations show the ET-TDT can be more powerful than other proposed methods under reasonable conditions. More importantly, our results show that, when multiple polymorphisms are found within the gene, the ET-TDT can be useful for determining which polymorphisms affect liability. Abstract | | |
| Powerful Multilocus Tests of Genetic Association in the Presence of Gene-Gene and Gene-Environment Interactions The American Journal of Human Genetics, Volume 79, Issue 6, 1 December 2006, Pages 1002-1016 Nilanjan Chatterjee, Zeynep Kalaylioglu, Roxana Moslehi, Ulrike Peters and Sholom Wacholder Abstract In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1–degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data. Abstract | | |
| A Fine-Scale Linkage-Disequilibrium Measure Based on Length of Haplotype Sharing The American Journal of Human Genetics, Volume 78, Issue 4, 1 April 2006, Pages 615-628 Yan Wang, Lue Ping Zhao and Sandrine Dudoit Abstract High-throughput genotyping technologies for SNPs have enabled the recent completion of the International HapMap Project (phase I), which has stimulated much interest in studying genomewide linkage-disequilibrium (LD) patterns. Conventional LD measures, such as D′ and r2, are two-point measurements, and their relationship with physical distance is highly noisy. We propose a new LD measure, Δ, defined in terms of the correlation coefficient for shared haplotype lengths around two loci, thereby borrowing information from multiple loci. A U-statistic–based estimator of Δ, which takes into consideration the dependence structure of the observed data, is developed and compared with an estimator based on the usual empirical correlation coefficient. Furthermore, we propose methods for inferring LD-decay rates and recombination hotspots on the basis of Δ. The results from coalescent-simulation studies and analysis of HapMap SNP data demonstrate that the proposed estimators of Δ are superior to the two most popular conventional LD measures, in terms of their close relationship with physical distance and recombination rate, their small variability, and their strong robustness to marker-allele frequencies. These merits may offer new opportunities for mapping complex disease genes and for investigating recombination mechanisms on the basis of better-quantified LD. Abstract | | |