Monte carlo markov chain methods for genome screening

Abstract
We used Monte Carlo Markov chain (MCMC) methods to analyze a quantitative trait, MAO level, and a discrete trait, Collaborative Study on the Genetics of Alcoholism (COGA) alcoholism. Segregation, linkage, and haplotype sharing were analyzed and effects of marker map features were examined. For MAO, modest signals were found on chromosomes 1 and 17 for raw data, and 15 for covariate-adjusted data. For alcoholism, a strong signal was found on chromosome 1 with modest signals on chromosomes 4 and 10.