Testing Strategies for Family-Based Studies in Genetics
Author Information
Author(s): Amy Murphy, Scott T. Weiss, Christoph Lange
Primary Institution: Brigham and Women's Hospital, Boston, Massachusetts, United States of America
Hypothesis
Can a two-stage testing strategy improve the power of family-based genetic studies where all offspring are affected?
Conclusion
The proposed testing strategy significantly increases statistical power compared to standard methods, allowing for the detection of genetic markers associated with childhood asthma.
Supporting Evidence
- The proposed testing strategy demonstrated substantial power increases over standard approaches.
- Two SNPs were identified as genome-wide significant that would not have been detected using standard methodology.
- The methodology allows for the assessment of genetic effect size independent of unknown allele frequency.
Takeaway
This study created a new way to find genes linked to diseases by using family data, which helps researchers see patterns better, especially when all family members have the same condition.
Methodology
The study used a two-stage testing strategy that first estimates genetic effect sizes from family data and then tests SNPs for association using adjusted significance levels.
Limitations
The method cannot be applied when there is no phenotypic variation among probands.
Participant Demographics
The study analyzed data from 1172 subjects in 403 families, all of whom had childhood asthma.
Statistical Information
P-Value
0.0032 for rs10863712, 0.0047 for rs1294497
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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