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In order to run the PhyloNet toolkit, you must have Java 1.78.0 or later installed on your system. All references to the java command assume that Java 1.7 is being used.
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Code Block |
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java -jar $PHYLONET_DIRECTORY/PhyloNet_X.Y.Z.jar script.nex |
Where $PHYLONET$PHYLONET_PATH DIRECTORY is the directory of jar file PhyloNet_X.Y.Z.jar, and script.nex
is the NEXUS file containing the commands to be executed.
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4.4.1 MCMC_SEQ: Bayesian inference on the sequence alignment data
Input NEXUS file | Maximum number of reticulations |
---|---|
0 | |
1 | |
2 | |
3 | |
4 |
Corresponding results: Fig 13 in the book chapter.
4.4.2 MCMC_GT: Bayesian inference on gene tree topologies
4.4.2.1 MCMC_GT sampling using true gene tree topologies
Input NEXUS file | Maximum number of reticulations |
---|---|
MCMC_GT_pl8_0_true.nex | 0 |
MCMC_GT_pl8_1_true.nex | 1 |
MCMC_GT_pl8_2_true.nex | 2 |
MCMC_GT_pl8_3_true.nex | 3 |
MCMC_GT_pl8_4_true.nex | 4 |
This inference ran out of 192 CPU hours.
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To use MCMC_SEQ, you need to download an additional package beagle to calculate Felsenstein Likelihood. Please follow "Installing from source".
Add this package to your java library, and load this library before you run PhyloNet.
One input example: mcmc_seq.nex
All input NEXUS files: download
Corresponding results: Fig 13 in the book chapter.
4.4.2 MCMC_GT: Bayesian inference on gene tree topologies
4.4.2.1 MCMC_GT sampling using true gene tree topologies
Input NEXUS file | Maximum number of reticulations |
---|---|
MCMC_GT_pl8_0_true.nex | 0 |
MCMC_GT_pl8_1_true.nex | 1 |
MCMC_GT_pl8_2_true.nex | 2 |
MCMC_GT_pl8_3_true.nex | 3 |
MCMC_GT_pl8_4_true.nex | 4 |
This inference ran out of 192 CPU hours.
4.4.2.2 MCMC_GT sampling using gene tree topologies estimated by IQTREE
Input NEXUS file | Maximum number of reticulations |
---|---|
MCMC_GT_pl8_0_false.nex | 0 |
MCMC_GT_pl8_1_false.nex | 1 |
MCMC_GT_pl8_2_false.nex | 2 |
MCMC_GT_pl8_3_false.nex | 3 |
MCMC_GT_pl8_4_false.nex | 4 |
This inference ran out of 192 CPU hours.
4.4.3 MCMC_BiMarkers: Bayesian inference on the bi-allelic markers
This method uses an additional package jeigen. You need to follow the instructions to install it, and add this package to your java library.
Input NEXUS file: mcmc_bimarker.nexus
This inference ran out of 192 CPU hours.
4.5 Analyzing Larger Data Sets
This section corresponds to section 5 in the book chapter.
4.5.1 Tree-based Augmentation
The -fs command in MP and MPL is to fix the start tree topology.
The following two examples are to infer a network using gene trees estimated by IQTREE and fixing the start species tree inferred by ASTRAL.
Input NEXUS file for MP: InferNetwork_MP_pl8_3_false_fs.nex
Input NEXUS file for MPL: InferNetwork_MPL_pl8_3_false_fs.nex
4.5.2 Divide-and-conquer
The data set contains the MCMC_SEQ outputs of 680 trinets. You need to download the data and change the path ".../DivideAndConquer/" in netmerger.nex.
Data: https://drive.google.com/file/d/1mJfqD0bQOOoBFZTlaQklHLqvJX5QPlVg/view?usp=sharing
Input NEXUS file: netmerger.nex
4.6 Analyzing Polyploids
This section corresponds to section 7 in the book chapter.
4.6.1 MDC Inference with unknown hybrid species
Input NEXUS file | Maximum number of reticulations |
---|---|
MCMCInferNetwork_GT_pl8_0_false.nex | 0 |
MCMC_GT_pl8_1_false.nex | 1 |
MCMC_GT_pl8_2_false.nex | 2 |
MCMC_GT_pl8_3_false.nex | 3 |
MCMC_GT_pl8_4_false.nex | 4 |
This inference ran out of 192 CPU hours.
4.4.3 MCMC_BiMarkers: Bayesian inference on the bi-allelic markers
Input NEXUS file: mcmc_bimarker.nexus
This inference ran out of 192 CPU hours.
4.5 Analyzing Larger Data Sets
This section corresponds to section 5 in the book chapter.
4.6 Analyzing Polyploids
Corresponding results: Fig 17 in the book chapter.
4.6.2 MDC Inference with known hybrid species
Input NEXUS file | Maximum number of reticulations | Specified hybrid species |
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InferNetwork_MP_1.nex | 1 | LPS168 |
InferNetwork_MP_2.nex | 2 | LPS168 |
InferNetwork_MP_2_2.nex | 2 | LPS168, LPS189 |
InferNetwork_MP_3.nex | 3 | LPS168 |
InferNetwork_MP_3_2.nex | 3 | LPS168, LPS189 |
Corresponding results: Fig 18 This section corresponds to section 7 in the book chapter.
5. Visualizing a Phylogenetic Network
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