Association mapping via a class of haplotype-sharing statistics
2007
Haplotype-sharing statistics for association mapping
Sample size: 200
publication
Evidence: moderate
Author Information
Author(s): Allen Andrew S, Satten Glen A
Primary Institution: Duke University
Hypothesis
Can haplotype-sharing statistics improve association mapping in genetic epidemiology?
Conclusion
Haplotype-based statistics provide greater power and better localization of risk loci compared to single-SNP analysis.
Supporting Evidence
- Haplotype-based methods yielded larger -log10(Pvalue) values than the TDT.
- Haplotype-based methods localized the risk locus effectively.
- The cross test performed best among all tests applied.
Takeaway
This study shows that using groups of genes (haplotypes) can help scientists find disease-causing genes better than looking at single genes.
Methodology
The study applied four haplotype-sharing tests to simulated data from Genetic Analysis Workshop 15, focusing on a specific region of chromosome 6.
Limitations
The small biases involved make it difficult to draw definitive conclusions.
Participant Demographics
200 trios from 100 families were analyzed.
Statistical Information
Statistical Significance
p<0.05
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