R/qtlbim: QTL with Bayesian Interval Mapping in experimental crosses

Brian S. Yandell, Tapan Mehta, Samprit Banerjee, Daniel Shriner, Ramprasad Venkataraman, Jee Young Moon, W. Whipple Neely, Hao Wu, Randy von Smith, Nengjun Yi

Research output: Contribution to journalArticlepeer-review

83 Scopus citations


Summary: R/qtlbim is an extensible, interactive environment for the Bayesian Interval Mapping of QTL, built on top of R/qtl (Broman et al., 2003), providing Bayesian analysis of multiple interacting quantitative trait loci (QTL) models for continuous, binary and ordinal traits in experimental crosses. It includes several efficient Markov chain Monte Carlo (MCMC) algorithms for evaluating the posterior of genetic architectures, i.e. the number and locations of QTL, their main and epistatic effects and gene-environment interactions. R/qtlbim provides extensive informative graphical and numerical summaries, and model selection and convergence diagnostics of the MCMC output, illustrated through the vignette, example and demo capabilities of R (R Development Core Team 2006).

Original languageEnglish (US)
Pages (from-to)641-643
Number of pages3
Issue number5
StatePublished - Mar 2007
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


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