Handles multi-locus hypotheses by computing the posterior probability of a hypothesis. BNPP allows users to compute the posterior probability of multi-locus models. It represents models where a single locus by itself is associated with a phenotype such as a disease by using particular types of Bayesian network (BN) structures. This tool computes the posterior probability of a model based on the likelihoods of these structures and their prior probabilities.
Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA; Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA; Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA
BNPP funding source(s)
Supported by [grant number 1K99LM010822-01] and [grant number R01-LM010020] from the National Library of Medicine at the National Institutes of Health.