Mapping Complex Disease Loci Using Family-Based Association Tests
Author Information
Author(s): Juan Pablo Lewinger, Sophia SF Lee, Joanna Biernacka, Long Yang Wu, Haijiang Steven Shi, Shelley B Bull
Primary Institution: Samuel Lunenfeld Research Institute, Mount Sinai Hospital
Hypothesis
Can a two-stage strategy improve the mapping of complex disease loci?
Conclusion
The study found that certain confidence intervals always contained the true disease loci and that the likelihood ratio test provided strong evidence of their presence.
Supporting Evidence
- The bootstrap confidence intervals based on the peak Zlr and the 1-LOD support always contained the true disease loci.
- The likelihood ratio test provided strong confirmatory evidence of the presence of disease loci.
- Family-based association tests showed significant results in regions spanned by SNP packets.
Takeaway
The researchers used a two-step method to find where diseases might come from in genes, and it worked well in their tests.
Methodology
The study used simulated data to perform genome scans and family-based association tests to identify disease loci.
Potential Biases
Potential biases due to the reliance on simulated data and specific population characteristics.
Limitations
The study's findings may not generalize beyond the simulated data used.
Participant Demographics
Simulated populations used in the Genetic Analysis Workshop 14.
Statistical Information
P-Value
2.2 × 10-5
Confidence Interval
95%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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