The classic TDT is a matched chi-square but the same data can be analyzed using a Maximum-Likelihood statistic (ML-TDT) which was shown to be more powerful. We propose an extension of the ML-TDT to quantitative phenotypes, denoted as ML-QTDT. As already proposed for linkage analysis (Alcais and Abel
Abstracts from the Tenth Annual Meeting of the International Genetic Epidemiology Society
- Publisher
- John Wiley and Sons
- Year
- 2001
- Tongue
- English
- Weight
- 72 KB
- Volume
- 21
- Category
- Article
- ISSN
- 0741-0395
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โฆ Synopsis
We developed a method to identify candidate regions in the search for disease susceptibility loci, based on contrasting the level of haplotype diversity of a sample of 'affected' chromosomes with that of an equal number of 'unaffected' chromosomes coming from the same population. Our approach involves the selection of trios (mother, father, child), each trio from a different family, both the child and one of the parents being affected. The affected chromosomes (cases) are defined as those inherited by the child from the affected parent, and the unaffected chromosomes (controls) are those inherited by that child from the unaffected parent. In the presence of linkage disequilibrium, the affected chromosome set will show a reduced level of haplotype diversity, or an excess of haplotype sharing. We consider sliding-window haplotypes of 2, 3, 4, n contiguous markers, and determine the haplotype frequency spectra (the distribution of the number of haplotypes observed in 1, 2, ..., n individuals) in the two chromosome sets for each n-marker haplotype. Heterogeneity between spectra is tested by chi-square. This method is appropriate for autosomal dominant or codominant diseases that do not substantially reduce Darwinian fitness, and is more suitable for situations where densely typed, evenly spaced maps of markers are available, as in the case of fine-mapping studies.
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