Related Experiment Videos
Statistical validity of the Haseman-Elston sib-pair test in small samples
1Department of Biometry and Genetics, Louisiana State University Medical Center, New Orleans 70112.
Genetic Epidemiology
|January 1, 1993
Summary
The Haseman-Elston sib-pair test for quantitative trait linkage is valid for small sample sizes. Using specific degrees of freedom maintains statistical accuracy, even with reduced marker heterozygosity.
Area of Science:
- Genetics
- Biostatistics
- Statistical genetics
Background:
- The Haseman-Elston sib-pair test is a common method for detecting linkage between genetic markers and quantitative traits.
- Evaluating the statistical validity of this test, particularly in smaller sample sizes, is crucial for accurate genetic analysis.
Purpose of the Study:
- To determine the empiric type I error rate of the Haseman-Elston sib-pair test in samples with 60 or fewer sib pairs.
- To assess the impact of marker-locus heterozygosity on the test's statistical validity.
Main Methods:
- Simulation experiments were conducted to evaluate the type I error rate.
- The Haseman-Elston test was applied to a quantitative trait and five unlinked markers.
- Two different methods for calculating degrees of freedom for the t-distribution were used and compared.
Main Results:
- Empiric type I error rates were slightly liberal when degrees of freedom were calculated based on the number of sib pairs per sibship (sigma s(i)(s(i) - 1)/2 - 2).
- When degrees of freedom were based on the number of sibs minus 1 per sibship (sigma (s(i) - 1) - 2), estimated empiric p-values closely matched nominal p-values.
- Reduced marker-locus heterozygosity did not elevate the empiric type I error rate in small samples.
Conclusions:
- The Haseman-Elston sib-pair test demonstrates acceptable statistical validity for linkage analysis in small sample sizes when appropriate degrees of freedom are used.
- The choice of degrees of freedom significantly impacts the test's type I error rate, with sigma (s(i) - 1) - 2 being more accurate.
- Marker heterozygosity levels do not compromise the test's reliability in small sample settings.