Difference between revisions of "JModelTest"
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jModelTest is a tool to carry out statistical selection of best-fit models of nucleotide substitution. It implements five different model selection strategies: hierarchical and dynamical likelihood ratio tests (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC), and a decision theory method (DT). It also provides estimates of model selection uncertainty, parameter importances and model-averaged parameter estimates, including model-averaged tree topologies. jModelTest 2 includes High Performance Computing (HPC) capabilities and additional features like new strategies for tree optimization, model-averaged phylogenetic trees (both topology and branch lenght), heuristic filtering and automatic logging of user activity. | jModelTest is a tool to carry out statistical selection of best-fit models of nucleotide substitution. It implements five different model selection strategies: hierarchical and dynamical likelihood ratio tests (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC), and a decision theory method (DT). It also provides estimates of model selection uncertainty, parameter importances and model-averaged parameter estimates, including model-averaged tree topologies. jModelTest 2 includes High Performance Computing (HPC) capabilities and additional features like new strategies for tree optimization, model-averaged phylogenetic trees (both topology and branch lenght), heuristic filtering and automatic logging of user activity. | ||
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| − | + | Run <code>module spider {{#var:app}}</code> to find out what environment modules are available for this application. | |
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==System Variables== | ==System Variables== | ||
| − | * HPC_{{uc:{{#var:app}}}}_DIR | + | * HPC_{{uc:{{#var:app}}}}_DIR - installation directory |
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{{#if: {{#var: conf}}|==Configuration== | {{#if: {{#var: conf}}|==Configuration== | ||
Revision as of 13:56, 13 June 2022
Description
jModelTest is a tool to carry out statistical selection of best-fit models of nucleotide substitution. It implements five different model selection strategies: hierarchical and dynamical likelihood ratio tests (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC), and a decision theory method (DT). It also provides estimates of model selection uncertainty, parameter importances and model-averaged parameter estimates, including model-averaged tree topologies. jModelTest 2 includes High Performance Computing (HPC) capabilities and additional features like new strategies for tree optimization, model-averaged phylogenetic trees (both topology and branch lenght), heuristic filtering and automatic logging of user activity.
Environment Modules
Run module spider jmodeltest to find out what environment modules are available for this application.
System Variables
- HPC_JMODELTEST_DIR - installation directory
Additional Information
To run jModelTest from the command-line load the jmodeltest module and use the 'jmodeltest' command in place of 'java -jar jModelTest.jar' command specified in the manual. You can use the jar file directly if you want, of course. It's located at $HPC_JMODELTEST_DIR/jModelTest.jar. Make sure to use the '-tr X' option where 'X' is the number of threads to use. The default is 8. Make sure your job script requests appropriate number of computing cores with the '#PBS -l nodes=1:ppn=X'.
To run a short interactive jModelTest session use the gui.rc.ufl.edu machine.