期刊
HUMAN HEREDITY
卷 55, 期 2-3, 页码 79-85出版社
KARGER
DOI: 10.1159/000072312
关键词
genome scan; quantitative trait loci; generalized least squares estimation; generalized estimating equations; permutation test
资金
- NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR003655] Funding Source: NIH RePORTER
- NCRR NIH HHS [RR 03655] Funding Source: Medline
- NIGMS NIH HHS [GM 28365] Funding Source: Medline
Haseman and Elston (H-E) proposed a robust test to detect linkage between a quantitative trait and a genetic marker. In their method the squared sib-pair trait difference is regressed on the estimated proportion of alleles at a locus shared identical by descent by sib pairs. This method has recently been improved by changing the dependent variable from the squared difference to the mean-corrected product of the sib-pair trait values, a significantly positive regression indicating linkage. Because situations arise in which the original test is more powerful, a further improvement of the WE method occurs when the dependent variable is changed to a weighted average of the squared sib-pair trait difference and the squared sib-pair mean-corrected trait sum. Here we propose an optimal method of performing this weighting for larger sibships, allowing for the correlation between pairs within a sibship. The optimal weights are inversely proportional to the residual variances obtained from the two different regressions based on the squared sib-pair trait sums, respectively, allowing for correlations among sib pairs. The proposed method is compared with the existing extension of the H-E approach for larger sibships. Control of the type I error probabilities for sibships of any size can be improved by using a generalized estimating equation approach and the robust sandwich estimate of the variance, or a Monte-Carlo permutation test. Copyright (C) 2003 S. Karger AG, Base I trait differences and the squared sib-pair mean-corrected.
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