BUCKy: Gene tree/species tree reconciliation with Bayesian concordance analysis
- B. Larget, Satish K. Kotha, Colin N. Dewey, C. Ané
- BiologyBioinform.
- 15 November 2010
AVILABILITY BUCKy is a C++ program that implements Bayesian concordance analysis that uses a non-parametric clustering of genes with compatible trees, and reconstructs the primary concords from clades supported by the largest proportions of genes.
Bayesian estimation of concordance among gene trees.
- C. Ané, B. Larget, D. Baum, Stacey D. Smith, A. Rokas
- BiologyMolecular biology and evolution
- 9 November 2006
A novel 2-stage Markov chain Monte Carlo (MCMC) method that first obtains independent Bayesian posterior probability distributions for individual genes using standard methods and introduces a one-parameter probability distribution to describe the prior distribution of concordance among gene trees.
A linear-time algorithm for Gaussian and non-Gaussian trait evolution models.
We developed a linear-time algorithm applicable to a large class of trait evolution models, for efficient likelihood calculations and parameter inference on very large trees. Our algorithm solves the…
TESTING FOR DIFFERENT RATES OF CONTINUOUS TRAIT EVOLUTION USING LIKELIHOOD
- B. O’Meara, C. Ané, M. Sanderson, P. Wainwright
- SociologyEvolution; international journal of organic…
- 1 May 2006
General predictions regarding changes in phenotypic diversity as a function of evolutionary history and rates are developed, and tests are derived to evaluate rate changes, showing that these tests are more powerful than existing tests using standardized contrasts.
Inferring Phylogenetic Networks with Maximum Pseudolikelihood under Incomplete Lineage Sorting
- Claudia R. Solís-Lemus, C. Ané
- BiologyPLoS Genetics
- 20 September 2015
This work presents a statistical method to infer phylogenetic networks from multi-locus genetic data in a pseudolikelihood framework and applies it to reconstruct the evolutionary relationships among swordtails and platyfishes, which is characterized by widespread hybridizations.
The iPlant Collaborative: Cyberinfrastructure for Plant Biology
- S. Goff, M. Vaughn, D. Stanzione
- Computer ScienceFrontiers in Plant Science
- 1 June 2011
These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.
Prospects for Building the Tree of Life from Large Sequence Databases
- A. Driskell, C. Ané, J. G. Burleigh, M. McMahon, B. O’Meara, M. Sanderson
- BiologyScience
- 12 November 2004
An analysis of two “supermatrices” suggests that even data sets with as much as 92% missing data can provide insights into broad sections of the tree of life.
PhyloNetworks: A Package for Phylogenetic Networks
- Claudia R. Solís-Lemus, P. Bastide, C. Ané
- BiologyMolecular biology and evolution
- 1 December 2017
PhyloNetworks is a Julia package for the inference, manipulation, visualization, and use of phylogenetic networks in an interactive environment and is the first software providing tools to summarize a set of networks with measures of tree edge support, hybrid edge Support, and hybrid node support.
Fast and accurate detection of evolutionary shifts in Ornstein–Uhlenbeck models
- M. Khabbazian, R. Kriebel, Karl Rohe, C. Ané
- Biology
- 1 July 2016
A phylogenetic lasso method to study trait evolution from comparative data and detect past changes in the expected mean trait values, using the Ornstein–Uhlenbeck process, which can model a changing adaptive landscape over time and over lineages.
Rphylopars: fast multivariate phylogenetic comparative methods for missing data and within‐species variation
- Eric W. Goolsby, J. Bruggeman, C. Ané
- Biology
- 1 January 2017
Rphylopars provides expanded capabilities over the original PhyloPars interface including a fast linear‐time algorithm, thus allowing for extremely large data sets to be analysed in seconds or minutes rather than hours, and introduces methods to estimate macroevolutionary parameters under alternative evolutionary models.
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