PT  - JOURNAL ARTICLE
AU  - Ming Fang
AU  - Michel Georges
TI  - BayesFM: a software program to fine-map multiple causative variants in GWAS identified risk loci
AID  - 10.1101/067801
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 067801
4099  - http://biorxiv.org/content/early/2016/08/04/067801.short
4100  - http://biorxiv.org/content/early/2016/08/04/067801.full
AB  - 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.