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rcolgem:
statistical inference and modeling of genealogies generated by epidemic and ecological processes

rcolgem is a package for phylodynamic inference using population genetic models. rcolgem implements coalescent models for populations with nonlinear dynamics and potentially many demes. Other population genetic models may be supported in the future. This package is well suited for studying infectious disease epidemics and inference of epidemiological parameters from pathogen phylogenies. The package could also be used for phylogeographic analysis and estimation of demographic histories (population size through time). Worked examples are provided for inferring transmission rates and R0 for a simple susceptible-infected-recovered (SIR) model and an HIV epidemic model.

rcolgem is not a package for conducting phylogenetic inference, although such packages are available in R (see phangorn) and such tools may be incorporated in the future. A time-scaled genealogy with known times of sampling is a necessary input for most functions in rcolgem.

Currently, rcolgem works best for fitting deterministic demographic models (e.g. systems of ordinary differential equations). Future versions may incorporate particle filters for fitting stochastic models. rcolgem also provides methods for simulating trees conditional on a demographic process.

Installation

install.packages("rcolgem", repos="http://R-Forge.R-project.org")
or, find precompiled packages here.

References

  • Volz EM, Koelle K, Bedford T, 2013, Viral Phylodynamics, PLOS Computational Biology, Vol:9, ISSN:1553-734X
  • Volz EM, 2012, Complex population dynamics and the coalescent under neutrality, Genetics, Vol:190, ISSN:0016-6731, Pages:187-201
  • Rasmussen DA, Volz EM, Koelle K, 2014, Phylodynamic Inference for Structured Epidemiological Models, PLOS Computational Biology, Vol:10, ISSN:1553-734X
  • Frost SDW, Volz EM, 2010, Viral phylodynamics and the search for an effective number of infections, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol:365, ISSN:0962-8436, Pages:1879-1890
  • Frost SDW, Volz EM, 2013, Modelling tree shape and structure in viral phylodynamics, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol:368, ISSN:0962-8436
  • Rasmussen, D. A., Ratmann, O., & Koelle, K. (2011). Inference for nonlinear epidemiological models using genealogies and time series. PLoS computational biology, 7(8), e1002136.
  • Volz EM, Ionides E, Romero-Severson EO, et al., 2013, HIV-1 Transmission during Early Infection in Men Who Have Sex with Men: A Phylodynamic Analysis, PLOS MEDICINE, Vol:10, ISSN:1549-1676
  • Volz EM, Kosakovsky Pond SL, Ward MJ, et al., 2009, Phylodynamics of infectious disease epidemics, Genetics, Vol:183, ISSN:0016-6731, Pages:1421-1430