Two-Step Strategy for Genome-Wide Association Studies
Author Information
Author(s): Hugues Aschard, Mickaël Guedj, Florence Demenais
Primary Institution: INSERM, U794
Hypothesis
Can a two-step multiple-marker strategy improve the efficiency of genome-wide association studies?
Conclusion
The proposed two-step multiple-marker strategy effectively identifies trait loci while minimizing false positives and the multiple testing problem.
Supporting Evidence
- The local score method revealed an average of 381 regions with positive scores.
- Five of the ten highest scoring regions were significant at the nominal 5% level.
- The average sensitivity of the multiple-marker strategy was over 94%.
Takeaway
This study shows a new way to look at many genetic markers at once, which helps find important genes without making too many mistakes.
Methodology
The study used a two-step approach: first, a local score method to identify candidate regions, and second, FBAT-LC to test these regions for association with traits.
Limitations
The study may not generalize to more complex interactions due to the focus on specific trait loci.
Participant Demographics
The study involved 1500 cases and 2000 controls in the case-control data, and 1500 affected sib pairs in the family data.
Statistical Information
P-Value
0.000000
Statistical Significance
p<0.05
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