{"entity": "researcher", "timestamp": "2026-09-28T23:05:21.474Z", "family": "Ali", "given": "Raja H", "initials": "RH", "orcid": "0000-0003-0539-3491", "affiliations": ["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."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/d9fb41310ab044279cb3331c744f56c3.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/d9fb41310ab044279cb3331c744f56c3"}}, "publications": [{"entity": "publication", "iuid": "fb84cabf32b940a1a5cdb784cc9a8a1d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/fb84cabf32b940a1a5cdb784cc9a8a1d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/fb84cabf32b940a1a5cdb784cc9a8a1d"}}, "title": "VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces.", "authors": [{"family": "Ali", "given": "Raja H", "initials": "RH", "orcid": "0000-0003-0539-3491", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d9fb41310ab044279cb3331c744f56c3.json"}}, {"family": "Bark", "given": "Mikael", "initials": "M"}, {"family": "Mir\u00f3", "given": "Jorge", "initials": "J"}, {"family": "Muhammad", "given": "Sayyed A", "initials": "SA"}, {"family": "Sj\u00f6strand", "given": "Joel", "initials": "J"}, {"family": "Zubair", "given": "Syed M", "initials": "SM"}, {"family": "Abbas", "given": "Raja M", "initials": "RM"}, {"family": "Arvestad", "given": "Lars", "initials": "L"}], "type": "journal article", "published": "2017-02-10", "journal": {"title": "BMC Bioinformatics", "issn": "1471-2105", "volume": "18", "issue": "1", "pages": "97", "issn-l": "1471-2105"}, "abstract": "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.\n\nWe 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.\n\nVMCMC 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/ .", "doi": "10.1186/s12859-017-1505-3", "pmid": "28187712", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC5301390"}, {"db": "pii", "key": "10.1186/s12859-017-1505-3"}], "notes": [], "created": "2018-12-05T13:01:06.635Z", "modified": "2026-09-23T10:44:48.504Z"}]}