Description
- Co-estimation of reticulate phylogenies (ILS & hybridization), gene trees, divergence times and population sizes on sequences from multiple independent loci.
- For species phylogeny or phylogenetic network, we infer network topology, divergence times in units of expected number of mutations per site, population sizes in units of population mutation rate per site, and inheritance probabilities.
- For gene trees, we infer gene tree topology and coalescent times in units of expected number of mutations per site.
- To convert the divergence times/coalescent times to units of years, or to coalescent units, see our paper for details (Page 3, Lines 36-43).
- We use BEAGLE, a high-performance library to calculate the "Felsenstein Likelihood". Full details of installation instructions can be found here, always follow "Installing from source".
If there is error, try command: java -Djava.library.path="/usr/local/lib" -jar PhyloNet_X.X.X.jar script.nex
Usage
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| MCMC Settings | ||
| -loci locusList | The list of loci used in the inference. For example, -loci (YNR008W,YNL313C) indicates the inference is performed on two loci YNR008W and YNL313C. See the format of multilocus data here. Note that our method is able to handle missing data, see the example below. | optional |
-cl chainLength | The length of the MCMC chain. The default value is 10,000,000. | optional |
| -bl burnInLength | The number of iterations in burn-in period. The default value is 2,000,000. | optional |
-sf sampleFrequency | The sample frequency. The default value is 5,000. | optional |
| -sd seed | The random seed. The default seed is 12345678. | optional |
| -pl parallelThreads | The number of threads running in parallel. The default value is the number of threads in your machine. | optional |
| -dir outDirectory | The absolute path to store the output files. The default path is your home directory. | optional |
| MC3 Settings | ||
| -mc3 temperatureList | The list of temperatures for the Metropolis-coupled MCMC chains. For example, -mc3 (2.0, 3.0) indicates two hot chains with temperatures 2.0 and 3.0 respectively will be run along with the cold chain with temperature 1.0. By default only the cold chain will be run. Note that
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| Inference Settings | ||
| -mr maxReticulation | The maximum number of reticulation nodes in the sampled phylogenetic networks. The default value is 4. | optional |
| -tm taxonMap | Gene tree / species tree taxa association. By default, it is assumed that only one individual is sampled per species in gene trees. This option allows multiple alleles to be sampled. For example, the gene tree is (((a1,a2),(b1,b2)),c); and the species tree is ((a,b),c);, the command is -tm <a:a1,a2; b:b1,b2;c:c>. Note that the taxa association should cover all species, e.g. -tm <a:a1,a2; b:b1,b2> is incorrect because c:c is dropped out. | optional |
| -fixps popSize | Fix the population sizes associated with all branches of the phylogenetic network to this given value. By default, we estimate a constant population size across all branches. | optional |
| -varyps | Vary the population sizes across all branches. By default, we estimate a constant population size across all branches. | optional |
| -murate | Enabling the delta exchange operator for modeling varying substitution rates across loci. | optional |
| Prior Settings | ||
| -pp poissonParam | The Poisson parameter in the prior on the number of reticulation nodes. The default value is 1.0. | optional |
| -dd | Disable the prior on the diameters of hybridizations. By default this prior on is exp(10). | optional |
| -ee | Enable the Exponential(10) prior on the divergence times of nodes in the phylogenetic network. By default we use Uniform prior. | optional |
| Starting State Settings | ||
| -sgt | Specify the starting gene trees for each locus. Comma delimited list of gene tree identifiers. See details. The gene trees should be ultrametric trees with coalescent times in units of expected number of mutations per site. See example below. The default starting gene trees are UPGMA trees. | optional |
| -snet | Specify the starting network. The input network should be ultrametric with divergence times in units of expected number of mutations per site, inheritance probabilities and population sizes in units of population mutation rate (optional). See example below. The default starting network is the MDC trees given starting gene trees. | optional |
| -sps | Specify the starting population size. The default value is 0.02. See example below. | optional |
| -pre | Specify the number of iterations for pre burn-in, e.g. "-pre 20" means 20x sampleFrequency iterations will be run before the MCMC chain starts. By default, we run 10x sampleFrequency iterations for pre burn-in. | optional |
Substitution Model | ||
| -gtr paramList | Set GTR (general time-reversible) as the substitution model. The first four parameters in the list represent base frequencies for A, C, G, T. The rest six parameters represent transition probabilities for A>C, A>G, A>T, C>G, C>T and G>T. The default substitution model is JC69 model. | optional |
| Phasing | ||
| -diploid diploidSpeciesList | Integrates over all possible phasings of heterozygous genotypes when computing likelihoods [2] given diploid species list. For example, a list of (Scer, Spar) indicates species Scer and Spar will be treated as diploid species in likelihood computation. See Section S4 in G-PhoCS manual for full details. By default we assume the sequences come from haploid species, or the sequences are randomly phased. Note that the substitution model is set to JC69 (fixed). | optional |
| Substitution rate sampling | ||
| -mupi paramList | Specify the substitution rates when sampling locus-specific substitution rates, which are a list of double values with the order of loci in the nexus file. The default value for all loci is 1.0. | |
| -muweight paramList | Specify the weights for substitution rates when sampling locus-specific substitution rates, which are a list of integer values with the order of loci in the nexus file. The default value for all loci is 1. | |
Simple Example
Download: MCMCseq_example0.nex
Please don't copy and paste, since some illegal characters might be copied.
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#NEXUS Begin data; Dimensions ntax=5 nchar=80; Format datatype=dna symbols="ACTG" missing=? gap=-; Matrix [YAL053W, 25, ...] Scer TCTTTATTGACGTGTATGGACAATT Spar TCTTTGTTAACGTGCATGGACAATT Smik TCCTTGCTAACATGCATGGACAATT Skud TCTTTGCTAACGTGCATGGATAATT Sbay TCTTTACTAACGTGCATGGATAACT [YAR007C, 30, ...] Scer ATGAGCAGTGTTCAACTTTCGAGGGGCGAT Spar ATGAGCAGCGTTCAACTTTCGAAGGGCGAC Smik ATGAGCAGCGTGCAACTATCAAAGGGCGAC Skud ATGAGCAGTGTTCAACTTTCGAAGGGCGAC Sbay ATGAGCAGCGTTCAACTTTCGAAGGGCGAC [YBL015W, 25, ...] Scer TCTAATTTGTTAAAGCAGAGAGTTA Spar TCTAATTTGTTAAAGCAGAGAGTTA Smik TCTAATTTGTTAAAACAGAGAGTTC Skud TCTAATCTGTTGAAGCAGAGAGTTA Sbay TCTAATCTGTTGAAGCAAAAAGTCA ;End; BEGIN PHYLONET; MCMC_SEQ -cl 250000 -bl 50000 -sf 5000; END; |
Example with Starting State
Download:
Please don't copy and paste, since some illegal characters might be copied.
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#NEXUS Begin data; Dimensions ntax=3 nchar=500; Format datatype=dna symbols="ACTG" missing=? gap=-; Matrix [0, 500] A TCGCGCTAACGTCGTTTATAAGTGATCAAAGATAAAAGGAAATCTAAGCTGCCTTCATGTTCCTCATCGGACCTGCACAAGGATGGGCGTGGAGATTCTGGCATGGATACTGTACTTTTACGCGATCGCCCCAGCTACCGACCTCTATAATCACAGGGAATCTCGGGGAACGAATTGCTTCACTAGGTCACACCCGGTTTATAGCCCGTAGAAGTTAGAGCCCGCGAATAAAGGACTAACAACTCTTATCAAGCTAAGGGACATCCTAGAGGGACCTCTGCGGGAGCAGCATGTTGTGTGACTCATCACGGTAAGAACTTGGCAAGCGCGACAGCGGCTAAGCCAGCATGCTAGGCGTCGTCGGATAGTCGCCGTCACGGAATCGGATGAGATCCCTTGAGGGATTGATGATGTTCACATCACTACATGGTTGTTCTGAGTGTTGGTGATCAGGTGCAGCAATTGTGCTTGACGGAAATGGGCTCTCATAACCGAACCCA C GCGCACCTCCCTCGGATATAAGTGACCGAAGAGAAAAGGGAATCTAATTGGCCCTATCATCACTCATCGTACCTGATCACGTATGGCTGTGGAGATTGCGGCATGGATACTGTACTTTTGAGCGATCATCCCAGTTACCGACCTTCTTAATAAGAGGGAACCTAGGGTAAAGGAATGCTCCACTCCGTCACACGGGGTATATATCCGGAATATGTTAGGCCCCCCGAATGAAGGAGTAAAAACTCTTAACAAGCTCCGACAGATCCTAGGGTATCGTCTGCGGGGCCGGCAGGTCGTGGGACGCATCACGCTAAACACTTGGCAAGCGTGACAGCGGCTGGGTCAGAATGCTCGGCCACGCCGTTTAGTCGCCGGCACCGAATCGAATGTGATCCCTTGAGGAAATGATGAAGTTAACATCATTACATGGGTGCTCTGAGTGATGGTGATAAGGTGGAGGACTTGTGTTTGACGGAAATGGGCTCTGAAAACCGAACTCT B GCGCACCTACTGCGGATATAAGTGACCGAAGAGTAATGGGAATCTATGCGGCCCTCGCGTCTCTCATCGTACCTGATCAAGTATGGGCGTGGAGATTGTGGCATGGATACTGTACTTTTGAGCCATCATCCCAGTTACCGACCTTCGTAATAAGAGCGAGCCTAGGGGAAAGAAATGCTCCACTCCATCACACCGGGTATATATCCGGAATATGTTCGAGCCCCCGAATAAAGGAGTAAAAACTCTTAACAAGCTCCGAAACATCCTAGGGTATCCTCTGCAGGGACGGCATGTTGTGGGGCCCATCACCCTAAGACCTTTGCAAGCATGAAAGCGGCTCAGCCAGCATGCTCGATCCCGCCGTACAGTCGCCGGCACGGAATCGAGTGTGATCCCCTGAGGAATTGATGAAGTTAACATCACTACTTGGCTGCTCTGAGTGCTGGTGATCAGGTGCAGCACATATGTGTGACGGAAATGGGCACTGACAACCGAACTAT [1, 500] A GAAACGGATCTAAGTGTACGGTTTCTCTCGAAGGGGGCACCTTTGCTATGCCCACCCCCATCTTGGAAGTGCGAGACCATACTCGCGCGTGCGTCAGGTTCTTACTTGATTTCGGCGGGGGTGGCTAAATTTTAGCTAGGGATCTAGAAATCCGTCATAGTCCTACAGGGCCATTCTGCCGCTTGCTAGCGTTGGTGATACGAGGGCAACTTTGAACTTTACGCGGAACTCCCCACCTCAGAGACTGTTACGACGTAGGCTAAATGTGCCGTGATTTCTGAGGGCAAAAGCCGTGCAAGGATGGACGGGGGTGCTCAAACAACTGCATCAGCCTCGGCATTATCTTGCATGAGCGCCTTCGATCGGTCACCAGTCGGCTAGATTACAAGCAAGCTCTTCGGAGGAGATGAGCTCGCATGGATCACGCGTCTACGTAACTTTCAGGGTCCATCCAAATGTCAATCATTCACCGAATGGCGATCGTCAGGTACGCGATTCCA C CGCTCGGATCTAAGTGTACGGTTTCTCTCGAAGGTGGAACCATTGCTATACCCACCCCCATCTTGGAAGTGCCAAACCATTCTCCCAAGAGCGTCGGGTTCTTACTCGATTTCGGCGGGGGTGGCTACAATTTAGGTAGGGATCTAGAAATCGGTTATAATCCTACAAAGCCATTCTGGCGCTTGCTAGTGTTGGTGATACGAGGGCAGCTTTGAACTTTACCGGGAACTGGGCACCTAAGGGACTGTGTCGACGTAGGCTAAATGTGCCGTGATTTCAGCGAGCAAAAGCCATGCAAGATTGGACGGGGGGCCTCAAACAACTGCATCAGCCTCGATATTATCTTGCATGAGCTCCTTCGATCGGTTCCCAGTCGGCTATATTATAAGCAAGCTCTTCGGAGGATATGAGCACGCACGGATTCCGCGTCTACGTAACTTTGAGGGCCCAGCCAGCAGTCAATCATTCAACGAATGGCGATCATAACGAACGCGATTCCA B CGCTCGGATCTAAGTGTACGGTTTCTCTGGAAGGTGGAACCATTGCTATACCCATCCCCATCTTGGAAGTGCCAGACCATTCTCCCAAGAGCGTCTGGTTCTTACTCGATTTCGGCGGGGGTGGCTACAATTTAGGTAGGGATCTAGAAATCGGTGATAATCGTACAAAGCCATTCTGGCGCTTGCTAGTGTCGGTGATACGAGAGCAGCTTTGAACTTTACCCGGAACTGCGCACCTAAGGGACTGTGTCGACGTAGGCTAAATGTGCCGTGATTTCAGCGAGCAAAAGCCATGCAAGATTGGACGGGCGGCCTCAAACAACTGCATCAGCCTCGATATTATCTTGCATGAGCTCCTTCGATCGGTTCCCAGTCGGCTATCTTATAAGCAAGCTCTTCGGAGGATATGAGCACGCACGGATTCCGCGTCTACGTAACTTTGAGGGCCCAGCCAGCAGTCAATCATTGACCGAATGGCGATCATAACGAACGCGATTCCA ;End; BEGIN TREES; Tree gt0 = (A:0.119900443,(C:0.058838639,B:0.058838639):0.061061803); Tree gt1 = (A:0.068766378,(C:0.016229589,B:0.016229589):0.052536789); END; BEGIN NETWORKS; Network net1 = (((B:0.0)I3#H1:0.05::0.8,(C:2.0E-8,I3#H1:2.0E-8::0.2)I2:0.04999998)I1:0.01,A:0.06)I0; END; BEGIN PHYLONET; MCMC_SEQ -cl 50000 -bl 10000 -sgt (gt0,gt1) -snet (net1) -sps 0.04 -pre 20; END; |
Example given Missing Data
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#NEXUS Begin data; Dimensions ntax=5 nchar=108; Format datatype=dna symbols="ACTG" missing=? gap=-; Matrix [loci1, 53, ...] a1 ATTGGAGACRAGCGARGACCGAGCTCACGAACCTGAGGAATGGAATCGATTAC a2 ATTTGAGACRAGCGARGACCGAGCTCACGAACCTGAGGANTGGAATCGATTAC b1 TTGGGAGACGAGCGAAGACAGAGCATATGAGCCTAAGGATTGGAATCGATTGT b2 TTGGGAGACGAGCGAAGACAGAGCATATGAGCCTGAGGATTGGAATCGATTGT [loci2, 58, ...] a2 ACTTTGCAAGCCAAAAATGGTATGCGAGACAACGCCTGTCATGGATGATGAACCAGAT b1 GCTTTGCAAGCCTAAGATGGTTTGCGAGACGACGATGGCAGTCGACGATGAATCAGAC b2 GCTTTGCAAGCCTAAGATGGTTTGCGAGACGACGATGGCAGTCGACGATGAATCAGAC c1 GCTTTGRAAGRCAAAAATGATATGCGAAACAACGCCCGTGATGGACGATGAACAGGAT ;End; BEGIN PHYLONET; MCMC_SEQ -loci (loci1,loci2) -cl 5000000 -bl 1000000 -tm <A:a1,a2; B:b1,b2; C:c1>; END; |
Understanding the Output
System Output
- Logger: each time a sample is collected, the program prints out
- first line: the Posterior value, current ESS (Effective Sample Size) based on the posterior values, likelihood value, prior value, current ESS based on the prior values.
- second line: the sampled phylogenetic network, with divergence times, population sizes and inheritance probabilities. Note that the value in the bracket is the population size of the root branch. If a constant population size across all branches is assumed, then the value represents the general population size.
- Summarization: the program prints out the chain length, burn-in length, sample frequency and the overall acceptance rate of proposals.
- Operations: the usage and the acceptance rate for each operation.
- 95% credible set of network topologies:
- size: the number of times the topology being sampled
- percent: the proportion of the topology being sampled
- MAP (Maximum A Posterior): the maximum posterior value and the corresponding topology the MAP topology are given.
- AVE: the average posterior value and the averaged (branch lengths and inheritance probabilities) network are printed out.
- rank: the topologies are ranked on their proportion.
- Run time: the elapsed time.
MCMC_SEQ -cl 250000 -bl 50000 -sf 5000 ----------------------- Logger: ----------------------- Overall MAP = -139.6655535361708 (((Spar:0.054401097303896875,Scer:0.054401097303896875):0.02940261095452569,Smik:0.08380370825842257):0.015640290731517764,(Sbay:0.038489186677349164,Skud:0.038489186677349164):0.060954812312591165); Total elapsed time : 27.35100 s |
Sample Files
The phylogenetic network, gene trees and the hyper-parameter of the population size are logged into files under your home directory or the directory specified by "-dir outDirectory".
- Phylogenetic Network: ~/outDirectory/network.log
- Hyper-parameter of Population size: ~/outDirectory/popSizePrior.log
- Gene tree: ~/outDirectory/tree_locusName.log
Downloads
- example.zip
- example.nexus: input file for PhyloNet
- example.txt: system output
- network.log, popSizePrior.log, tree_YAL053W.log, tree_YAR007C.log, tree_YBL015W.log: sample files
- The yeast data set (Rokas et al., 2003) sampled from seven Saccharomyces species S. cerevisiae (Scer), S. paradoxus (Spar), S. mikatae (Smik), S. kudriavzevii (Skud), S. bayanus (Sbay), S. castellii (Scas) and S. kluyveri (Sklu)
- The wheat data set (Marcussen et al., 2014) sampled from hexaploid bread wheat subgenomes T. aestivum TaA (A subgenome), TaB (B subgenome) and TaD (D subgenome), and five diploid relatives T. monococcum (Tm), T. urartu (Tu), Ae. sharonensis (Ash), Ae. speltoides (Asp) and Ae. tauschii (At)
- The mosquito data set (Fontaine et al., 2014) sampled from six Anopheles species An. gambiae (G), An. coluzzii (C), An. arabiensis (A), An. quadriannulatus (Q), An. merus (R) and An. melas (L)
Visualization
If you want to analyze parameters in the sampled networks using Tracer, please use command SummarizeMCMCResults to generate Tracer readable log file.
Command References
- D.Wen and L. Nakhleh. Co-estimating reticulate phylogenies and gene trees on sequences from multiple independent loci. Submitted.
- Gronau, Ilan, et al. Bayesian inference of ancient human demography from individual genome sequences. Nature genetics 43.10 (2011): 1031-1034.