title: Decision forest analysis of large-scale sib-pair identical-by-decent profiles for locating the underlying disease genes for alcoholism in human.
abstract: OBJECTIVE
  To extract the relevant SNPs for alcoholism using sib-pair IBD profiles of pedigrees.
  
  
  METHODS
  We used the ensemble decision approach, a supervised learning approach based on decision forests, to locate alcoholism relevant SNPs using genome-wide SNP data.
  
  
  RESULTS
  Application to a publicly available large dataset of 100 simulated replicates for three American populations (http://www.gaworkshop.org/) demonstrates that the proposed approach has successfully located all of the simulated true loci.
  
  
  CONCLUSIONS
  The numerical results establish the proposed decision forest analysis to be a powerful and practical alternative for large-scale family-based association study.
authors.affiliation: Department of Computer Science, Harbin Institute of Technology, Harbin 150080, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Li
authors.forename: Shao-qi
authors.initials: SQ
authors.lastname: Rao
authors.forename: Wei
authors.initials: W
authors.lastname: Zhang
authors.forename: Zheng
authors.initials: Z
authors.lastname: Guo
authors.forename: Wei
authors.initials: W
authors.lastname: Jiang
authors.forename: Lei
authors.initials: L
authors.lastname: Du
mesh_terms: D000437:Alcoholism / Q000235:genetics*; D001185:Artificial Intelligence; D003661:Decision Support Techniques; D006801:Humans; D008490:Medical Informatics / Q000379:methods*; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide