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Species delimitation using Markov Chain Monte Carlo

Pas-Kapli edited this page Jun 27, 2016 · 11 revisions

#Usage We provide a Markov Chain Monte Carlo sampling method for assessing the confidence of the Maximum Likelihood delimitation scheme. The MCMC method is activated with the --mcmc switch followed by the number of MCMC steps and the switch for either the PTP model (--single) or the mPTP model (--multi). The user may define a number of additional parameters for the MCMC sampling as explained below.

##Overview of Command-line Parameters

Parameter Explanation
--mcmc INT Support values for the delimitation (INT steps).
--mcmc_sample INT Sample every INT iteration (default: 1000).
--mcmc_log Log samples and create SVG plot of log-likelihoods.
--mcmc_burnin INT Ignore all MCMC steps below threshold.
--mcmc_chains INT Run multiple chains.
--mcmc_credible REAL Credible interval.
--mcmc_startnull Start each chain with the null model (one single species).
--mcmc_startrandom Start each chain with a random delimitation.
--mcmc_startml Start each chain with the delimitation obtained by the Maximum-likelihood heuristic.

The following command-line would execute a single MCMC analysis with 1 million steps and the mPTP :

$ mptp --tree_file tree_filename --output_file output_filename --mcmc 1000000 --multi --minbr 0.0009330519

Writing all MCMC samples into file is unnecessary and may produce large svg plot files (see output files). The --mcmc_sample option can be used for reducing the frequency of the MCMC sampling. For example, with the following command only the sampling frequency is set to 1/100, therefore 10000 files will be written in the output file.

$ mptp --tree_file tree_filename --output_file output_filename --mcmc 1000000 --multi --minbr 0.0009330519 --mcmc_sample 100

To o assess convergence (see convergence), it is important to run at least two independent MCMC analyses. This can be done in one mptp execution with the command --mcmc_chains followed by the number of analysis you want to run. It is highly recommended to run at least two independent runs, as shown in the command example below.

$ mptp --tree_file tree_filename --output_file output_filename --mcmc 1000000 --multi --minbr 0.0009330519 --mcmc_sample 100 --mcmc_chains 2

#Output Files

#Examples of Convergence

The figure below shows a case of convergence of two chains that were ran for 10 million generations with a sampling frequency of 10000.

convergence