SVDquartets: Singular Value Decomposition Scores for Species
Quartets: This program will compute scores based on the singular value
decomposition of a flattenning matrix of site pattern
probabilities for quartets of species. The score can effectively
differentiate which of the three possible quartet trees is the
true tree based on SNP data. The method is described in the
following papers:
Chifman, J. and L. Kubatko. 2014. Quartet inference from SNP data
under the coalescent, Bioinformatics 30(23): 3317-3324.
Chifman, J. and L. Kubatko. 2015. Identifiability of the unrooted
species tree topology under the coalescent model with time-reversible
substitution processes, Journal of Theoretical Biology 374: 35-47.
Swofford, D. L. and L. S. Kubatko. 2023. Species tree estimation using site pattern frequencies,
in Species Tree Inference: A Guide to Methods and Applications,
Chapter 4, pgs. 68-88, Princeton University Press [web link].
Click here
to download the software.
qAge: Estimation of speciation times under the multispecies coalescent: This method provides estimates
of the node times (or equivalently, the branch lengths) in a species-level phylogeny under the multispecies coalescent.
The method is described in the following papers:
Peng, J., D. Swofford, and L. Kubatko. 2022. Estimation of speciation times under the multispecies coalescent, Bioinformatics 38(23): 5182-5190
[web link].
Swofford, D. L. and L. S. Kubatko. 2023. Species tree estimation using site pattern frequencies,
in Species Tree Inference: A Guide to Methods and Applications,
Chapter 4, pgs. 68-88, Princeton University Press [web link].
The method is included in PAUP*, available here.
HyDe: Hybridization Detection: This program evaluates the hypothesis of hybrid speciation for sets of
three taxa and can be used to search for hybrid species in large data
sets. The method is described in the following papers:
Kubatko, L. and J. Chifman. 2019. An invariants-based
method for efficient identification of hybrid speciation from
large-scale genomic data, BMC Evolutionary Biology 19:112 [web link].
Blischak, P., J. Chifman, A. D. Wolfe,
and L. S. Kubatko. 2018. HyDe: a Python package for
genome-scale hybridization detection, Systematic Biology 67(5): 821-829 [web link].
Click here
to download the program.
rapidphylo: Rapidly Estimate Phylogeny from Large Allele Frequency Data Using Root Distances Method: This R
packages rapidly estimates tree-topology from large allele frequency data using Root Distances Method, under a Brownian Motion Model.
The method is described in the following paper:
Peng, J., H. Rajeevan, L. Kubatko, and A. RoyChoudhury. 2021. A fast likelihood approach for estimation of large phylogenies
from allele frequency data, Molecular Phylogenetics and Evolution 161: 107142 [web link].
Click here to link to the package on CRAN.
COALGF Calculator: COALGF Calculator is a C program that will compute the probability
distribution of gene tree histories and gene tree topolgies for a
fixed three-taxon species tree under the coalescent model with gene
flow between both pairs of sister population. This program was used
for all of the calculations in the paper:
Tian, Y. and L. Kubatko. 2016. Distribution of gene tree histories
under the coalescent model with gene flow, Molecular Phylogenetics and
Evolution 105: 177-192 [web link]; preliminary version available on
bioRxiv.
Click here to download the program.
SSA: Inference of Maximum Likelihood Phylogenetic Trees Using a Stochastic Search Algorithm: This program implements the stochastic search algorithm for estimation of phylogenetic trees under the maximum
likelihood criterion. It is described in the following paper for trees which satisfy the molecular clock, although
it can estimate non-clocklike trees as well:
Salter, L. and D. Pearl. 2001. A Stochastic Search Strategy for Estimation of Maximum Likelihood
Phylogenetic Trees, Systematic Biology 50(1): 7-17.
Click
here to download the program.
Phylogenetic Utility Programs: This includes programs to aid in the summary of the posterior distribution of phylogenetic trees from the program
MrBayes. The first program, post_prob, will tabulate the percentage of times each tree topology appears in the
posterior distribution output by MrBayes, thus providing posterior probabilities for each tree topology. The second
program, post_root, will tabulate the percentage of times each possible root position appears in the posterior
distribution output by MrBayes, thus providing posterior probabities for each root.
Click here to download these programs.
STEM-hy: Species Tree
Estimation using Maximum likelihood (with hybridization): STEM-hy is a program for inferring maximum likelihood species
trees
from a collection of estimated gene trees under the coalescent
model. It also carries out bootstrap analyses and can evaluate
hybridization hypotheses in a model selection framework.
Click here to download the program.
Click
here for slides from a tutorial on STEM and STEM-hy
from University of
Georgia, April 2012.
HybTree: A Perl Script for Estimating Hybridization and Time
Scales In the Presence of Deep Coalescence: Written by David Gerard for the analyses in the
following paper:
Gerard, D., H. L. Gibbs, and L. Kubatko. 2011. Estimating
hybridization in the presence of coalescence using phylogenetic
intraspecific sampling. BMC Evolutionary Biology,11: 291
[web link]
Click here to download the scripts.
COAL: Program for computing gene tree probabilities under the
coalescent process: Written by James Degnan (Ph.D., Spring 2005) - please see the COAL Website for more information
and to download the program.
FPRNET: Program for detecting gene regulatory networks from gene expression data using fuzzy logic, probability,
and regression methods: Written by Guy Brock (Ph.D., Summer 2003) - please see the
FPRNET website for more information and to download the program.
Analysis of High-throughput Proteomic Data: Programs to perform the analysis in the following reference are available:
Gilchrist, M., L. Salter, and A. Wagner. 2004. A statistical framework
for interpreting high-throughput proteomic datasets, Bioinformatics 20(5): 689-700.
Click here to download these programs.