The GA and the GWAS: using genetic algorithms to search for multilocus associations.
Enormous data collection efforts and improvements in technology have made large genome-wide association studies a promising approach for better understanding the genetics of common diseases. Still, the knowledge gained from these studies may be extended even further by testing the hypothesis that genetic susceptibility is due to the combined effect of multiple variants or interactions between variants. Here we explore and evaluate the use of a genetic algorithm to discover groups of SNPs (of size 2, 3, or 4) that are jointly associated with bipolar disorder. The algorithm is guided by the structure of a gene interaction network, and is able to find groups of SNPs that are strongly associated with the disease, while performing far fewer statistical tests than other methods.
Oregon Health & Science University, Portland.
Michael
M
Mooney
Beth
B
Wilmot
The
T
Bipolar Genome Study
Shannon
S
McWeeney
D000465:Algorithms; D001714:Bipolar Disorder / Q000235:genetics; D003198:Computer Simulation; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000379:methods*; D023281:Genomics / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide; D015203:Reproducibility of Results; D057170:Translational Research, Biomedical