• ExploreHypothesis_GibbsSampling
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Description

Using Gibbs Sampling to test the hypothesis given a collection of gene trees.

The network must be specified in the Rich Newick FormatThe gene trees must be rooted.

The input gene trees can be gene tree distributions inferred from Bayesian methods like MrBayes.

Usage

network_ident

The name of the network. See details.

mandatory

geneTreeList

Comma delimited list of gene tree identifiers or comma delimited list of sets of gene tree identifiers. See details.

mandatory

-a taxaMap

Gene tree / species tree taxa association.

optional

-cl chainLengthThe length of the Gibbs Sampling. The default value is 11,000.optional
-bl burnInLengthThe number of iterations in burn-in period. The default value is 1,000.optional
-sf sampleFrequencyThe sample frequency. The default value is 100.optimal

-pt pruningThreshold

The threshold of inheritance probabilities for pruning the reticulation edges in sampled networks. The default value is 0.01.

optional

-mb maxBranchLength

Maximum branch lengths used in Gibbs Sampling. The default value is 6.

optional

-psd 

Using pseudo-likelihood instead of full likelihood.

optional

-pl numberOfThreads

The number of threads used in the computation. The default value is 1.

optional

-di

Output the resulting networks in the format that can be read by Dendroscope .

optional

resultOutputFile

Optional file destination for command output.

optional

The method will output all the samples collected along with their posterior. At last, all the sampled networks will be pruned by removing reticulation edges whose inheritance probabilities are lower than a threshold. The default value of this threshold is 0.01. Users can change it through option -pt. 

By default, it is assumed that only one individual is sampled per species in gene trees. However, the option [-a taxaMap] allows multiple alleles to be sampled.

By default, the full likelihood is used in this method. If the dataset is out of the scope of full-likelihood computation, users can use pseudo-likelihood instead through option -psd.

If users want to run the computation in parallel. Please specify the number of processors through option -pl.

Note that when the program is running, you may see some outputs generated by a optimization library we are using. In order to ignore these, it is recommended to use the optional output file. 

Examples

Command References

  • Y. Yu, C. Jermaine, and L. Nakhleh. Exploring Phylogenetic Hypotheses via Gibbs Sampling on Evolutionary Networks. Under Review. 2016.

See Also

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