Adaptive Two-Stage Analysis for Genome-Wide Association Studies
Author Information
Author(s): Song Kijoung, Lu Qing, Lin Xiwu, Waterworth Dawn, Elston Robert C
Primary Institution: GlaxoSmithKline and Case Western Reserve University
Hypothesis
Can the adaptive two-stage analysis improve the detection of susceptibility loci in genome-wide association studies?
Conclusion
The adaptive two-stage analysis effectively identified susceptibility disease genes in a small sample size after Bonferroni correction.
Supporting Evidence
- The ATS analysis captured significant regions associated with susceptibility loci on chromosome 6.
- Results showed that the ATS had good performance compared to other methods.
- Bonferroni correction was applied to control for multiple testing.
Takeaway
Researchers created a new test to find genes linked to diseases by looking at DNA variations, and it worked well even with a small number of samples.
Methodology
The study used an adaptive two-stage analysis combining the Hardy-Weinberg disequilibrium trend test and the Cochran-Armitage trend test on simulated data.
Limitations
The ATS method is more costly and computationally intensive than other two-stage analyses.
Participant Demographics
200 cases with rheumatoid arthritis and 200 controls were randomly selected from a larger dataset.
Statistical Information
P-Value
2.7 × 10-15
Statistical Significance
p<0.05
Want to read the original?
Access the complete publication on the publisher's website