Analyses of single marker and pairwise effects of candidate loci for rheumatoid arthritis using logistic regression and random forests.

ABSTRACT: Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid Arthritis Consortium (NARAC) candidate gene data set (Problem 2), analyzing 463 independent patients and 855 controls. Specifically, our work examined the correspondence between logistic regression (LR) analysis of single-locus and pairwise interaction effects, and random forest (RF) single and joint importance measures. For this comparison, we selected small but stable RFs (500 trees), which showed strong correlations (r~0.98) between their importance measures and those by RFs grown on 5000 trees. Both RF importance measures captured most of the LR single-locus and pairwise interacti

SUBMITTER: Glaser B 

PROVIDER: S-EPMC2367457 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature