title: Information-theoretic gene-gene and gene-environment interaction analysis of quantitative traits.
abstract: BACKGROUND
  The purpose of this research was to develop a novel information theoretic method and an efficient algorithm for analyzing the gene-gene (GGI) and gene-environmental interactions (GEI) associated with quantitative traits (QT). The method is built on two information-theoretic metrics, the k-way interaction information (KWII) and phenotype-associated information (PAI). The PAI is a novel information theoretic metric that is obtained from the total information correlation (TCI) information theoretic metric by removing the contributions for inter-variable dependencies (resulting from factors such as linkage disequilibrium and common sources of environmental pollutants).
  
  
  RESULTS
  The KWII and the PAI were critically evaluated and incorporated within an algorithm called CHORUS for analyzing QT. The combinations with the highest values of KWII and PAI identified each known GEI associated with the QT in the simulated data sets. The CHORUS algorithm was tested using the simulated GAW15 data set and two real GGI data sets from QTL mapping studies of high-density lipoprotein levels/atherosclerotic lesion size and ultra-violet light-induced immunosuppression. The KWII and PAI were found to have excellent sensitivity for identifying the key GEI simulated to affect the two quantitative trait variables in the GAW15 data set. In addition, both metrics showed strong concordance with the results of the two different QTL mapping data sets.
  
  
  CONCLUSIONS
  The KWII and PAI are promising metrics for analyzing the GEI of QT.
authors.affiliation: Department of Pharmaceutical Sciences, State University of New York, Buffalo, NY, USA. pchanda@cse.buffalo.edu
authors.forename: Pritam
authors.initials: P
authors.lastname: Chanda
authors.forename: Lara
authors.initials: L
authors.lastname: Sucheston
authors.forename: Song
authors.initials: S
authors.lastname: Liu
authors.forename: Aidong
authors.initials: A
authors.lastname: Zhang
authors.forename: Murali
authors.initials: M
authors.lastname: Ramanathan
mesh_terms: D000465:Algorithms; D000818:Animals; D050197:Atherosclerosis / Q000235:genetics; D019295:Computational Biology; D004777:Environment; D005260:Female; D005796:Genes; D006801:Humans; D007108:Immune Tolerance / Q000528:radiation effects; D008075:Lipoproteins, HDL / Q000235:genetics; D008297:Male; D051379:Mice; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics; D019655:Quantitative Trait, Heritable; D014466:Ultraviolet Rays
chemical_list: D008075:Lipoproteins, HDL