GppDxy: GppDxy: function to simulate posterior predictive simulated...

In radamsRHA/GppFst: Posterior Predictive Simulations for generating theoretical distributions of Fst and Dxy under the neutral coalescent model for two species

Description

This function returns a vector of dxy values simulated from a posterior distribution

Usage

GppDxy(posterior.samples, loci.per.step, sample.vec.0, sample.vec.1,
  sequence.length.vec)

Arguments

posterior.samples	List of posterior samples with columns for single column for each parameter and a row for each step of the MCMC chain [see read.posterior]
loci.per.step	Number of genealogies to simulate for each joint parameter combination of the posterior MCMC chain
sample.vec.0	List of number of sampled individuals for population 0 for each locus in the empirical distribution
sample.vec.1	List of number of sampled individuals for population 1 for each locus in the empirical distribution
sequence.length.vec	List of the locus length for each locus in the empirical dataset; can be set to c(190,190) to simulate all loci with length of 190 nucleotides

Examples

## Not run: 
library(GppFst)
library(Geneland)
library(phybase)

experimental_params <- read.table(file = '~/Desktop/GppFST_Tutorial/ExperimentalParameters.txt', header = T) # Read tab-delimited file with experimental parameters
pop0.samples <- experimental_params$pop0.samples # Extract pop0 samples per empirical locus
pop1.samples <- experimental_params$pop1.samples # Extract pop1 samples per empirical locus
locus.lengths <- experimental_params$locus.length # Extract locus lengths per empirical locus

MCMC.samples <- read.posterior(posterior.file = '~/Desktop/GppFST_Tutorial/atrox_snap_gamma2.log', format = "tab", burnin = .95)

Gppdxy.results <- GppDxy(posterior.samples = MCMC.samples, loci.per.step = 10, sample.vec.0 = pop0.samples, sample.vec.1 = pop1.samples, sequence.length.vec = locus.lengths)
mean(as.numeric(Gppdxy.results) # get mean
hist(as.numeric(Gppdxy.results) # plot distribution

## End(Not run)

radamsRHA/GppFst documentation built on Nov. 9, 2019, 7:08 p.m.