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Detecting gene-gene interactions that underlie human diseases.
1Institute of Human Genetics, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne NE1 3BZ, UK. heather.cordell@ncl.ac.uk
Nature Reviews. Genetics
|May 13, 2009
Summary
Detecting genetic interactions beyond single genes is crucial for understanding complex human diseases. This review surveys methods and software for identifying these genetic effects and their biological relevance.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Genome-wide association (GWA) studies identify single genetic variants linked to disease.
- Standard analyses may miss complex genetic interactions influencing disease risk.
- Understanding these interactions is key to elucidating disease pathways.
Purpose of the Study:
- To critically review methods for detecting interactions between genetic loci in human diseases.
- To survey available software packages for analyzing genetic interactions.
- To discuss challenges in establishing the biological relevance of detected statistical interactions.
Main Methods:
- Literature review of statistical and computational methods.
- Survey of software tools for genetic interaction analysis.
- Discussion of biological validation strategies.
Main Results:
- Several methods and software packages exist for detecting genetic locus interactions.
- These methods can increase the power to detect disease associations.
- Challenges remain in interpreting the biological significance of statistical interactions.
Conclusions:
- Analyzing genetic interactions is essential for a comprehensive understanding of human genetic diseases.
- The development and application of robust analytical tools are ongoing.
- Further research is needed to bridge statistical findings with biological mechanisms.
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