We use likelihood-based score statistics to test for association between a disease and a diallelic polymorphism, based on data from arbitrary types of nuclear families. The Nonfounder statistic extends the transmission disequilibrium test (TDT) to accommodate affected and unaffected offspring, missi
Exact family-based association tests for biallelic data
✍ Scribed by Kady Schneiter; Nan Laird; Chris Corcoran
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 134 KB
- Volume
- 29
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Family‐based study designs have an important role in the search for association between disease phenotypes and genetic markers. Unlike traditional case‐control methods, family‐based tests use within‐family data to avoid identification of spurious associations that may result from population admixture. Many family‐based association tests have been proposed to accommodate a variety of ascertainment schemes and patterns of missing data. In this report, we describe exact family‐based association tests for biallelic data. Specifically, we discuss test of the null hypotheses “no linkage and no association” and “linkage, but no association”. These tests, which are valid under various models for inheritance and patterns of missingness, utilize the procedure proposed by Rabinowitz and Laird [2000: Hum Hered 50:211–223] that provides a unified framework for family based association testing (FBAT). The conditioning approach implemented in FBAT makes an exact test conceptually straightforward, but computationally difficult since the minimum sufficient statistics upon which we condition do not have a conventional form. An exact test may be especially critical when accurate computation of the extreme area of the FBAT statistic is needed, such as when the study design necessitates multiple comparisons adjustments. We describe the exact approach as a useful alternative to the aymptotic test and show that the exact tests for biallelic data may be most useful for the recessive disease model. Genet. Epidemiol. 2005 © 2005 Wiley‐Liss, Inc.
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