Improving Candidate Gene Analysis in Genome-Wide Studies
Author Information
Author(s): Curtis David, Vine Anna E, Knight Jo
Primary Institution: Queen Mary's School of Medicine and Dentistry
Hypothesis
How can we better analyze candidate genes in the context of genome-wide association studies?
Conclusion
Formal procedures are necessary to ensure that results from candidate regions are not overshadowed by numerous nominally significant results from routine markers.
Supporting Evidence
- Candidate markers should be treated differently from routine markers to avoid important findings being overlooked.
- The proposed method uses prior probabilities to rank markers for further investigation.
- A candidate marker significant at p = 0.01 should be considered similarly to a routine marker significant at p = 0.00001.
Takeaway
When scientists look for genes that might cause diseases, they need to pay special attention to certain genes instead of just looking at all the data together, so they don't miss important findings.
Methodology
The study proposes a method to rank candidate gene markers differently from routine markers based on prior probabilities and likelihood ratios.
Potential Biases
There is a risk that important findings from candidate genes may be overlooked due to the overwhelming number of routine markers.
Limitations
The proposed method relies on arbitrary prior probabilities and may not account for all complexities in genetic association.
Statistical Information
P-Value
0.01
Statistical Significance
p<0.01
Digital Object Identifier (DOI)
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