The interaction index, a novel information-theoretic metric for prioritizing interacting genetic variations and environmental factors |
| |
| Authors: | Pritam Chanda Lara Sucheston Aidong Zhang Murali Ramanathan |
| |
| Affiliation: | 1Department of Computer Science and Engineering, State University of New York, Buffalo, NY, USA;2Department of Biostatistics, State University of New York, Buffalo, NY, USA;3Department of Pharmaceutical Sciences, State University of New York, Buffalo, NY, USA |
| |
| Abstract: | We developed an information-theoretic metric called the Interaction Index for prioritizing genetic variations and environmental variables for follow-up in detailed sequencing studies. The Interaction Index was found to be effective for prioritizing the genetic and environmental variables involved in GEI for a diverse range of simulated data sets. The metric was also evaluated for a 103-SNP Crohn''s disease dataset and a simulated data set containing 9187 SNPs and multiple covariates that was modeled on a rheumatoid arthritis data set. Our results demonstrate that the Interaction Index algorithm is effective and efficient for prioritizing interacting variables for a diverse range of epidemiologic data sets containing complex combinations of direct effects, multiple GGI and GEI. |
| |
| Keywords: | gene–environment interactions gene–gene interactions K-way interaction information |
|
|
