GARLI Version 0.96 Beta
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GARLI (Genetic Algorithm for Rapid Likelihood Inference) performs phylogenetic searches on aligned sequence datasets using the maximum-likelihood criterion. Version 0.96 is a major revision from the previous version 0.951. It includes many new features, including the ability to perform tree inference using amino acid and codon-based models, in addition to the standard nucleotide-based models available in previous versions. On a practical level, the program is able to perform maximum-likelihood tree searches on large datasets in a number of hours.
GARLI is written and maintained by Derrick Zwickl (email@example.com).
A support and information website is available here.
Inquiries and support questions may be sent to firstname.lastname@example.org.
New in version 0.961. Rigorous reading of Nexus datasets using Paul Lewis and Mark Holder's Nexus Class Library (NCL)
2. Ability to read Nexus starting trees using NCL
3. Ability to perform inference under amino acid and codon-based models of sequence evolution (datatype = aminoacid, datatype = codon)
4. Ability to specify multiple search replicates in a single config file (searchreps = #)
5. Ability to specify outgroups for orientation of inferred trees (outgroup = # # #)
6. Ability to use backbone as well as normal topological constraints
7. Ability to create fast likelihood stepwise addition starting trees (streefname = stepwise)
8. MPI version that spreads a specified number of serial runs across processors using a single config file, writing output to different output files (for example, to do 25 bootstrap replicates simultaneously on each of 8 processors)
9. Ability to perform nucleotide inference using any sub-model of the General Time-Reversible model (GTR), in addition to all of the common "named" models (K2P, HKY, etc)
10. Speed increases for non-parametric bootstrapping
Substitution models available in version 0.96 include:
- Nucleotide models: All models nested within the General Time Reversible (GTR) model, optionally with discrete gamma distributed rate heterogeneity and/or an inferred proportion of invariable sites.
- Amino acid models: Many of the well known fixed amino acid rate matrices (Dayhoff, Jones, WAG, mtRev, mtmam), with either fixed or observed (aka "+F") amino acid frequencies, and discrete gamma distributed rate heterogeneity and/or an inferred proportion of invariable sites
- Codon models: The basic Goldman and Yang (1994) model and other related models, with a number of options for codon frequencies (equal, "F1x4", "F3x4", observed) and one or more estimated non-synonymous rate categories (aka dN/dS or omega parameters)
GARLI is loosely based on the program GAML, by Paul O. Lewis (1998). It uses a stochastic genetic algorithm-like approach to simultaneously find the topology, branch lengths and substitution model parameters that maximize the log-likelihood (lnL). This involves the evolution of a population of solutions termed individuals, with each individual encoding a tree topology, a set of branch lengths and a set of model parameters. Each individual is assigned a fitness based on its lnL score. Each generation random mutations are applied to some of the components of the individuals, and their fitnesses are recalculated. The individuals are then chosen to be the parents of the individuals of the next generation, in proportion to their fitnesses. This process is repeated many times, and the population of individuals evolves toward higher fitness solutions.
NOTE: The OS X graphical version of GARLI that was previously available for version 0.951 has not yet been updated for version 0.96, but will be soon.