LPhyRevPy

Convert LPhy models to RevBayes script.

Usage

Python 3.9 or higher. Depend on numpy, scipy, typing, inspect, pprint, and Bio (Biopython).

This project is currently in development. Please check out the source code to run init.py under the project root. Prefer to run using IDE, such as PyCharm.

Usage:

__init__.py -i <inputfile> -o <outputfile>

Example

Rev tutorial https://revbayes.github.io/tutorials/coalescent/constant

LPhy:

data {
  D = readFasta(file="data/horses_isochronous_sequences.fasta");
  taxa = D.taxa();
  L = D.nchar();
}
model {
  Θ ~ LogNormal(meanlog=3.0, sdlog=1.0);
  ψ ~ Coalescent(theta=Θ, taxa=taxa);
  π ~ Dirichlet(conc=[1.0,1.0,1.0,1.0]);
  rates ~ Dirichlet(conc=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0]);
  Q=gtr(freq=π, rates=rates);
  γ ~ LogNormal(meanlog=0.0, sdlog=2.0);
  r ~ DiscretizeGamma(shape=γ, ncat=4, replicates=L);
  clock ~ LogNormal(meanlog=-16.88, sdlog=5.0);
  D ~ PhyloCTMC(tree=ψ, siteRates=r, Q=Q, mu=clock);
}

Rev:

D <- readDiscreteCharacterData("data/horses_isochronous_sequences.fasta")
taxa := D.taxa()
Theta ~ dnLognormal(mean=3.0, sd=1.0)
psi ~ dnCoalescent(theta=Theta, taxa=taxa)
rates ~ dnDirichlet(alpha=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
pi ~ dnDirichlet(alpha=[1.0, 1.0, 1.0, 1.0])
Q := fnGTR(exchangeRates=rates, baseFrequencies=pi)
clock ~ dnLognormal(mean=-16.88, sd=5.0)
gamma ~ dnLognormal(mean=0.0, sd=2.0)
r := fnDiscretizeGamma(shape=gamma, rate=gamma, numCats=4)
D_clamp ~ dnPhyloCTMC(tree=psi, Q=Q, branchRates=clock, siteRates=r)
D_clamp.clamp(D)

More examples

Available conversions

1. Read sequences, and create taxa
2. Commonly used nucleotide substitution models
3. Constant sized coalescent model
4. Basic birth-death model
5. Basic PhyloCTMC
6. Commonly used prior distributions
7. IID
8. Method calls

TODO

1. Rev Moves
2. Vector match
3. Discrete phylogeography
4. Structured coalescent
5. More birth-death models
6. https://revbayes.github.io/tutorials/coalescent/
7. New parameter of https://revbayes.github.io/tutorials/coalescent/skyline
8. Individual TODOs inside some Python classes