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1.Installation.Rmd
2.Input_files.Rmd
3.Generate_set_of_models.Rmd
3a.How_models_are_built.Rmd
3b.Plotting_models.Rmd
4.Subsample_CreateInput.Rmd
5.Run_Phrapl.Rmd
6.Post-processing.Rmd
7.SensitivityAnalyses.Rmd
README.md
phrapl_logo.png

README.md

PHRAPL -- user manual

Please send me an email if you have comments.


PHRAPL project web site

CITATION

OTHER REFERENCES

CODE

PHRAPL is written in R, but it uses perl and ms to perform simulations. The pre-CRAN (code under development) can be found in github.

Why to use PHRAPL?

Phylogeographic research aims to understand the recent history of species. Over the last decades, researchers have increasingly incorporated demographic models in order to estimate parameters (i.e., divergence times, population sizes, and rates of migration and expansion) that can contribute phylogeographic inference. Typically, this is conducted via the use of software packages that contain specified models (n-island models or fixed topologies). Alternatively, simulation-based approaches allow researchers to customize models for the particular details of their system, and may be useful in testing preexisting biogeographic hypotheses. Because the demographic model is central to the analysis in either case, researchers may wish to assess the appropriateness of their model to the data. PHRAPL is designed to give such a tool to researchers.

How PHRAPL works?

PHRAPL simulates genealogies under a wide range of demographic models and compares the empirical genealogies to the simulated gene tree distributions. Demographic models that are probable given the data will contain many genealogies that match the estimated gene trees. Because the proportion of matching gene trees for a given model is equivalent to the probability of the data given the model and parameter values, we can use this value in an information theoretic framework to evaluate the relative weight of all models. This provides the researcher with an independent assessment of both the best model, given the data as well as the ability to calculate the model likelihoods of classes of models (e.g., n-island vs. isolation models).

Watch these YouTube videos to learn more about PHRAPL.

Contents

  1. Installation
  • Phydocker for windows users: It lets you use PHRAPL without having to install R, perl, ms, etc, just docker. Recommended only for testing.
  1. Input files
  2. Generate a set of models (migrationArray object)
  1. Subsampling and creating an input for PHRAPL
  2. Running PHRAPL (GridSearch option)
  3. Post-processing

Advanced topics:

  1. Sensitivity Analyses
  2. Species delimitation (in construction)

Do you have a question about PHRAPL or want to report a bug?

Post it in the phrapl-users google group.