https://github.com/cboettig/wrightscape

:package: Infer adaptive landscapes from phylogenetic trees

https://github.com/cboettig/wrightscape

Science Score: 36.0%

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:package: Infer adaptive landscapes from phylogenetic trees

Basic Info
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  • Stars: 3
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  • Open Issues: 1
  • Releases: 2
Created about 16 years ago · Last pushed almost 9 years ago
Metadata Files
Readme License

README.md

DOI

wrightscape

A fast C code implementation of maximum likelihood calculations for a multi-peak OU process with independent alpha, sigma, and theta parameters for each peak on phylogenetic trees (an extension of the ouch model). Includes R package wrapper as interface to C code. Likelihood calculation presented in http://www.carlboettiger.info/files/phylo-covariance.pdf, later the basis for: Jeremy M. Beaulieu, Dwueng-Chwuan Jhwueng, Carl Boettiger and Brian O’Meara, (2012). Modeling Stabilizing Selection: Expanding the Ornstein-Uhlenbeck Model of Adaptive Evolution, Evolution 66 (8) 2369-2383. doi:10.1111/j.1558-5646.2012.01619.x

File overview

regimes.c: Test the regimes data structure Modify to handle a single regime Implement a transition density calculation where transitions occur at nodes alone <<< Pagel & Meade, Huelsenbeck papers -- what about transitions at nodes?

linear.c: BM not really subset of OU, as alpha = 0 not acceptible OU calculation. Modify the OU model to handle appropriately small alpha with Taylor Expansion or as BM

max likelihood: Implement and test maximum likelihood searches over parameters against existing methods

mcmc.c: Start implementing a basic MCMC solver!

matrix_method.c: nonlinear transition densities?
Test the stationary distribution?

Error handling

This should probably be done mostly at the R level, enforcing the strict formats and conventions of the input (i.e. if not doing regimes, all states should be listed at 0. States must be numbered incrementally from 0 to n-1, where n is the number of regimes present.)

STEPPING STONES

  • Recursive Joint Prob method using BM, compare to analyticals
  • Bayesian OU vs BM in RJMCMC
  • Use Pagel's BayesTraits run to "paint tree" with uncertainty, then repeat OUCH analysis with uncertainty in branch color

Owner

  • Name: Carl Boettiger
  • Login: cboettig
  • Kind: user
  • Company: UC Berkeley

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