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Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
Saurabh Ghosh1, Sarah Bertelsen, Theodore Reich
1Department of Psychiatry, Washington University School of Medicine, St, Louis, Missouri, USA. saurabh@isical.ac.in
Background:
Compared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze total cholesterol level in the younger cohort (the offspring generation) of the Genetic Analysis Workshop 13 simulated data set.
Results:
We obtained significant evidence of linkage near four of the six non-sex-specific genes in at least 30% of the replicates.
Conclusions:
The proposed nonparametric method seems to be a powerful robust alternative to distribution-based methods.
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