r2VIM: A new variable selection method for random forests in genome-wide association studies

Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (...

Source: BioData Mining - February 1, 2016 Category: Bioinformatics Authors: Silke Szymczak, Emily Holzinger, Abhijit Dasgupta, James D. Malley, Anne M. Molloy, James L. Mills, Lawrence C. Brody, Dwight Stambolian and Joan E. Bailey-Wilson Source Type: research