TY - JOUR T1 - BayesFM: a software program to fine-map multiple causative variants in GWAS identified risk loci JF - bioRxiv DO - 10.1101/067801 SP - 067801 AU - Ming Fang AU - Michel Georges Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/08/04/067801.abstract N2 - We herein describe a new method to fine-map GWAS-identified risk loci based on the Bayesian Least Absolute Shrinkage Selection Operator (LASSO) combined with a Monte Carlo Markov Chain (MCMC) approach, and corresponding software package (BayesFM). We characterize the performances of BayesFM using simulated data, showing that it outperforms standard forward selection both in terms of sensitivity and specificity. We apply the method to the NOD2 locus, a well-established risk locus for Crohn’s disease, in which we identify 13 putative independent signals. ER -