Decision forest analysis of large-scale sib-pair identical-by-decent profiles for locating the underlying disease genes for alcoholism in human.
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.
Li
Xia
X
Department of Computer Science, Harbin Institute of Technology, Harbin 150080, China.
Rao
Shao-qi
SQ
Zhang
Wei
W
Guo
Zheng
Z
Jiang
Wei
W
Du
Lei
L
D000437:Alcoholism / Q000235:genetics*; D001185:Artificial Intelligence; D003661:Decision Support Techniques; D006801:Humans; D008490:Medical Informatics / Q000379:methods*; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide