Decision forest analysis of large-scale sib-pair identical-by-decent profiles for locating the underlying disease genes for alcoholism in human

Beijing Da Xue Xue Bao Yi Xue Ban. 2006 Feb 18;38(1):71-3.

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.

Conclusion: The numerical results establish the proposed decision forest analysis to be a powerful and practical alternative for large-scale family-based association study.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alcoholism / genetics*
  • Artificial Intelligence
  • Decision Support Techniques*
  • Humans
  • Medical Informatics / methods*
  • Pedigree
  • Polymorphism, Single Nucleotide