Genomic Screening in Family-Based Association Testing
Author Information
Author(s): Amy Murphy, Matthew B. McQueen, Jessica Su, Peter Kraft, Ross Lazarus, Nan M. Laird, Christoph Lange, Kristel Van Steen
Primary Institution: Harvard School of Public Health
Hypothesis
Can a novel screening technique improve the identification of genetic markers associated with disease susceptibility in family-based association testing?
Conclusion
The study suggests that both univariate and multivariate testing methodologies are useful in detecting genotype-phenotype associations.
Supporting Evidence
- The screening technique identified SNPs with significant associations in both univariate and multivariate analyses.
- TSC0047225 was consistently identified across different testing methodologies.
- The study highlights the importance of using multiple screening techniques to validate genetic associations.
Takeaway
Researchers used a new method to find genetic markers that might be linked to diseases by looking at family data, and they found some promising results.
Methodology
The study utilized family-based association testing (FBAT) and a screening technique to analyze SNP data from 1,613 subjects across 143 families.
Potential Biases
Potential bias from multiple comparisons and the reliance on specific phenotypic measurements.
Limitations
The findings may not be replicable and could be influenced by noise in the data.
Participant Demographics
Approximately 1,613 subjects from 143 families, with a mixture of large and small pedigrees.
Statistical Information
P-Value
0.004
Statistical Significance
p<0.01
Digital Object Identifier (DOI)
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