Adjusting LOD Scores for Non-Normal Traits in Bivariate Linkage Analysis
Author Information
Author(s): Buil Alfonso, Dyer Thomas D, Almasy Laura, Blangero John
Primary Institution: Southwest Foundation for Biomedical Research
Hypothesis
Can we find a robust LOD score approximately proportional to the LOD score under model misspecification with the bivariate phenotype?
Conclusion
A smoothing correction can improve the accuracy of LOD scores in bivariate linkage analysis with non-normally distributed phenotypes.
Supporting Evidence
- The study found that variance component methods increase type I error for non-normally distributed traits.
- A robust LOD score correction was developed for bivariate phenotypes.
- Simulation results indicated that 1,000 to 3,000 replicates are sufficient for reliable slope estimation.
Takeaway
When studying traits that don't follow normal patterns, we need to adjust our calculations to get better results.
Methodology
The study used simulation methods to adjust LOD scores for bivariate phenotypes from the COGA dataset.
Potential Biases
Potential bias due to the non-normal distribution of the phenotypes studied.
Limitations
The method may be too conservative and requires further validation.
Participant Demographics
The study focused on White non-Hispanic individuals from 143 extended families.
Digital Object Identifier (DOI)
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