Abstract
There are a number of human diseases that are caused by the epistatic Interaction of multiple genes. Detecting these interactions with standard statistical tools is difficult, because there may be an interaction effect, but minimal or no main effect. Reconstructability analysis uses Shannon's information theory to detect relationships between variables in categorical datasets. We apply reconstructability analysis to data generated by five different models of gene-gene interaction, with heritability levels from 0.053 to 0.008, using 200 controls and 200 cases. We find that even with heritability levels as low as 0.008, and with the inclusion of 50 non-associated genes in the data-set, we can identify the interacting gene pairs with an accuracy of 80% or better.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2102-2106 |
| Number of pages | 5 |
| Journal | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 3 |
| State | Published - Dec 1 2005 |
| Event | IEEE Systems, Man and Cybernetics Society, Proceedings - 2005 International Conference on Systems, Man and Cybernetics - Waikoloa, HI, United States Duration: Oct 10 2005 → Oct 12 2005 |
Keywords
- Epistasis
- Gene interaction modeling
- Gene-gene interaction
- Genetics
- Information theory
- Occam
- Reconstructability analysis
ASJC Scopus subject areas
- Engineering(all)