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Species delimitation using Markov Chain Monte Carlo
#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.