Computational methods for single-point and multipoint analysis of genetic variants associated with a simulated complex disorder in a general population.
Several techniques for association analysis have been applied to simulated genetic data for a general population. We describe and compare the performance of three single-point methods and two multipoint approaches rooted in machine learning and data mining.
Shoemaker
C A
CA
Department of Computer Science, Worcester Polytechnic Institute, Worcester, Massachusetts, USA.
Pungliya
M
M
Sao Pedro
M A
MA
Ruiz
C
C
Alvarez
S A
SA
Ward
M
M
Ryder
E F
EF
Krushkal
J
J
D000483:Alleles; D001185:Artificial Intelligence; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D014644:Genetic Variation; D005828:Genetics, Population; D005838:Genotype; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D015999:Multivariate Analysis; D016571:Neural Networks, Computer