The key feature of GARLI 2.0 is that it allows you to partition your data. The basic instructions for using this feature can be found in the GARLI manual here. To try to ease the pain of making this work within the CIPRES Science Gateway design, we have created two separate tools to run complex analyses over several partitions. The first interface, called GARLI 2.0 on XSEDE, is designed to completely configure and run analyses with no partitions, or with multiple partitions that are evaluated under a single model.
The GARLI 2.0 on XSEDE interface will allow you to analyze multiple partitions under different models, but it cannot configure the garli.conf file required. We recommend users create this file using the second interface offered here, called GARLI.conf Creator. This interface will help you configure and print a garli.conf file with up to 5 separate partitions. If you require more partitions, it is fairly straightforward (though perhaps tedious) to edit a garli.conf file with as many partitions as you require.
Running a partitioned data set in GARLI 2.0 requires:
Important Facts:
Set searchreps= and bootstrapreps= in a garli.conf file as follows:
If searchreps is 2 or more, and bootstrapreps=0, enter searchreps=1 in the [general] section of the garli.conf file.
If bootstrapreps is greater than 0, enter bootstrapreps=1 in the [master] section of the garli.conf file; and set searchreps to the desired value in the[general] section of the garli.conf file.
If you plan to upload a starting tree file, enter the value streefname = starting.txt in the [general] section of the garli.conf file. Remove any other lines with the value streefname = <anything>.
If you plan to upload a starting tree file, enter the value constraintfile = constraint.txt in the [general] section of the garli.conf file. Remove any other lines with the value constraintfile = <anything>.
Input Files:
Starting Trees (optional): These may be provided in Newick or Nexus format.
Constraint files (optional): These can be represented in Newick or an alternative format. See the GARLI Manual here for a complete discussion.
Output files: The file garli_run.run00.boot.tre contains the best scoring tree in the set of replicates (2 by default) for bootstrap 00. For each bootstrap requested, there will be a corresponding file name, where the number 00 is incremented 1,2,3, etc up to 99 (if you ran 100 bootstraps). Each such file contains the best tree found for the replicates in the respective BS run.
The file “allBootTrees.tre “ assembles the best tree from each bootstrap into a single Nexus file for convenience of downloading. You must take the trees assembled in allBootTrees.tre and calculate the consensus tree outside of GARLI. The author suggests SumTrees, PAUP*, CONSENSE of the Phylip package or Phyutility. Other options exist.You can use Consense in the CIPRES Science Gateway to perform this operation. First you must save the allBootTrees.tre file to your current folder using the button provided at the top of the page when you view that file. Next, convert the allBootTrees.tre file to Phylip format using NCL converter, specifying input format as Nexus and output format as Phylip. When the job completes, save the output file out.tre to your folder with the button provided. Finally, run Consense on this file.
If you have a local version of PAUP*, the GARLI wiki provides further help on how to accomplish this using PAUP*.
Dr. Zwickl is currently a postdoctoral researcher at the University of Kansas
GARLI home page here.
INPUT = DNA or protein matrices in Nexus or non-interleaved Phylip format
The table below shows the kinds of results returned by CIPRES Science Gateway
Input File Names | Sample File from a Test |
input file | garli_input.nex |
parameter file | garli.conf |
Sample Output File Type | File Name |
screen_dump bootstrap 00 | garli_run.run00.screen.log |
best score every x generations, bootstrap 00 | garli_run.run00.log00.log |
best tree found in each set of replicates bootstrap 00 | garli_run.run00.boot.tre |
best trees from all bootstraps in one file | allBootTrees.tre |
If you use GARLI, please cite:
Zwickl, D. J. (2006) Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion. Ph.D. dissertation, The University of Texas at Austin. (pdf)
If there is a tool or a feature you need, you can add it yourself or let us know.