Detecting Disease-Associated Genotype Patterns
Author Information
Author(s): Long Quan, Zhang Qingrun, Ott Jurg
Primary Institution: Beijing Institute of Genomics, Chinese Academy of Sciences
Hypothesis
Can a new method effectively detect disease-causing single-locus effects and gene-gene interactions?
Conclusion
The new method is effective for detecting disease susceptibility variants with small main effects and strong interaction effects.
Supporting Evidence
- The method is superior to traditional single-locus approaches.
- It can estimate the number of disease variants in a dataset.
- The method was applied successfully to datasets on Parkinson Disease and heroin addiction.
Takeaway
The researchers created a new way to find genetic patterns that can cause diseases, which is better than just looking at one gene at a time.
Methodology
The method involves detecting differences in genotype pattern frequencies between case and control individuals using logistic regression.
Limitations
The method cannot handle missing observations.
Participant Demographics
104 former severe heroin addicts and 101 control individuals, all Caucasians.
Statistical Information
P-Value
0.0005
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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