transmission disequilibrium test;
linkage;
association;
power analysis;
D O I:
10.1002/gepi.1018
中图分类号:
Q3 [遗传学];
学科分类号:
071007 ;
090102 ;
摘要:
Transmission disequilibrium test (TDT) is a nuclear family-based analysis that can test linkage in the presence of association. It has gained extensive attention in theoretical investigation and in practical application; in both cases, the accuracy and generality of the power computation of the TDT are crucial. Despite extensive investigations, previous approaches for computing the statistical power of the TDT are neither accurate nor general. In this paper, we develop a general and highly accurate approach to analytically compute the power of the TDT. We compare the results from our approach with those from several other recent papers, all against the results obtained from computer simulations. We show that the results computed from our approach are more accurate than or at least the same as those from other approaches. More importantly, our approach can handle various situations, which include (1) families that consist of one or more children and that have any configuration of affected and nonaffected sibs; (2) families ascertained through the affection status of parent(s); (3) any mixed sample with different types of families in (1) and (2); (4) the marker locus is not a disease susceptibility locus; and (5) existence of allelic heterogeneity. We implement this approach in a user-friendly computer program: TDT Power Calculator. Its applications are demonstrated. The approach and the program developed here should be significant for theoreticians to accurately investigate the statistical power of the TDT in various situations, and for empirical geneticists to plan efficient studies using the TDT. (C) 2001 Wiley-Liss, Inc.
机构:
Univ Utah, Hlth Sci Ctr, Eccles Inst Human Genet, Salt Lake City, UT 84112 USAUniv Utah, Hlth Sci Ctr, Eccles Inst Human Genet, Salt Lake City, UT 84112 USA
机构:
Univ Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA
Univ Calif San Francisco, Dept Radiol & Biomed Imaging, San Francisco, CA 94143 USAUniv Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA
Sebro, Ronnie
Rogus, John J.
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机构:
Joslin Diabet Ctr, Sect Genet & Epidemiol, Div Res, Boston, MA 02215 USAUniv Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA