title: VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces.
abstract: BACKGROUND
  MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters.
  
  
  RESULTS
  We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines.
  
  
  CONCLUSIONS
  VMCMC is a free software available under the New BSD License. Executable jar files, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/ .
authors.affiliation: KTH Royal Institute of Technology, Swedish e-Science Research Centre, Science for Life Laboratory, School of Computer Science and Communication, Solna, SE-171 77, Sweden.
authors.forename: Raja H
authors.identifier: http://orcid.org/0000-0003-0539-3491
authors.initials: RH
authors.lastname: Ali
authors.affiliation: KTH Royal Institute of Technology, School of Information and Communication Technology, Kista, SE-164 40, Sweden.
authors.forename: Mikael
authors.initials: M
authors.lastname: Bark
authors.affiliation: KTH Royal Institute of Technology, School of Information and Communication Technology, Kista, SE-164 40, Sweden.
authors.forename: Jorge
authors.initials: J
authors.lastname: Miró
authors.affiliation: KTH Royal Institute of Technology, Swedish e-Science Research Centre, Science for Life Laboratory, School of Computer Science and Communication, Solna, SE-171 77, Sweden.
authors.forename: Sayyed A
authors.initials: SA
authors.lastname: Muhammad
authors.affiliation: Department of Numerical Analysis and Computer Science, Swedish e-Science Research Centre, Science for Life Laboratory, Stockholm University, Stockholm, SE-100 44, Sweden.
authors.forename: Joel
authors.initials: J
authors.lastname: Sjöstrand
authors.affiliation: KTH Royal Institute of Technology, Laboratory for Communication Networks, School of Electrical Engineering, Stockholm, SE-100 44, Sweden.|Department of Computer Science and Information Technology, University of Balochistan, Quetta, PK-87 300, Pakistan.
authors.forename: Syed M
authors.initials: SM
authors.lastname: Zubair
authors.affiliation: Department of Computer Science and Engineering, University of Gothenburg, Gothenburg, SE-411 37, Sweden.
authors.forename: Raja M
authors.initials: RM
authors.lastname: Abbas
authors.affiliation: Department of Numerical Analysis and Computer Science, Swedish e-Science Research Centre, Science for Life Laboratory, Stockholm University, Stockholm, SE-100 44, Sweden. arve@nada.su.se.
authors.forename: Lars
authors.initials: L
authors.lastname: Arvestad
mesh_terms: D008390:Markov Chains; D009010:Monte Carlo Method; D010802:Phylogeny; D012984:Software
keywords: Convergence; Markov chain Monte Carlo; Metropolis-Hastings; Phylogenetics; Software; Visualization