James P Roney1, Jeremy Ferlic2,3, Franziska Michor2,3,4,5,6, Thomas O McDonald2,3,4. 1. Harvard College, Cambridge MA 02138, USA. 2. Department of Data Sciences, Center for Cancer Evolution, Dana-Farber Cancer Institute. 3. Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA. 4. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA. 5. The Broad Institute of Harvard and MIT, Cambridge, MA 02139, USA. 6. The Ludwig Center at Harvard, Boston, MA 02215, USA.
Abstract
SUMMARY: ESTIpop is an R package designed to simulate and estimate parameters for continuous-time Markov branching processes with constant or time-dependent rates, a common model for asexually reproducing cell populations. Analytical approaches to parameter estimation quickly become intractable in complex branching processes. In ESTIpop, parameter estimation is based on a likelihood function with respect to a time series of cell counts, approximated by the Central Limit Theorem for multitype branching processes. Additionally, simulation in ESTIpop via approximation can be performed many times faster than exact simulation methods with similar results. AVAILABILITY AND IMPLEMENTATION: ESTIpop is available as an R package on Github (https://github.com/michorlab/estipop). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: ESTIpop is an R package designed to simulate and estimate parameters for continuous-time Markov branching processes with constant or time-dependent rates, a common model for asexually reproducing cell populations. Analytical approaches to parameter estimation quickly become intractable in complex branching processes. In ESTIpop, parameter estimation is based on a likelihood function with respect to a time series of cell counts, approximated by the Central Limit Theorem for multitype branching processes. Additionally, simulation in ESTIpop via approximation can be performed many times faster than exact simulation methods with similar results. AVAILABILITY AND IMPLEMENTATION: ESTIpop is available as an R package on Github (https://github.com/michorlab/estipop). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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