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BAMSE is a software for performing association studies of multiple SNPs and environmental factors. We have developed a method based on Bayesian statistics that can model interactions for a large number of SNPs and environmental risk factors while accounting for the multiple testing problem. More specifically we have developed a Markov Chain Monte Carlo method that allows for identification of sets of SNPs and environmental factors that when combined increase disease risk or change the distribution of a quantitative trait. In this method, combinations of genetic and environmental genetic factors define risk sets. Individuals with genotypes that are members of a risk set have modified distributions of disease risk or quantitative trait value. Phenotypic traits are modelled using normal distributions (quantitative traits) or binary traits (case control). A Markov chain is established with state space on the set of all possible risk sets and parameters (e.g. mean and variance) of trait value distributions for each risk set. The stationary distribution of the Markov chain is given by the posterior density of risk sets and trait value distributions. Statistical inferences are based on this posterior distribution. The Markov chain is simulated by the Metropolis-Hastings algorithm using reversible jumps, to jump between risk sets. This method differs fundamentally from previous approaches by entertaining non-linear models and by addressing the multiple testing problem in a computationally and statistically efficient manner. The method is developed for unrelated individuals


download folder

  • For Windows:

download the folder

  • For Linux:

download the BAMSE.linux folder

  • test files (for both linux and windows) are in the folder

test files

  • The source code is in the folder source
  • All files and folder are in the file
  • manual