Phylogenetics: Large Scale Maximum Likelihood Analyses
|EEB 349: Phylogenetics|
|This lab explores two programs (GARLI and RAxML) designed specifically for maximum likelihood analyses on a large scale (hundreds of taxa).|
Part A: Starting a GARLI run on the cluster
GARLI is a program written by Derrick Zwickl for estimating the phylogeny using maximum likelihood, and is currently one of the best programs to use if you have a large problem (i.e. many taxa). GARLI now (as of version 0.96) gives you considerable choice in substitution models: GTR[+I][+G] or codon models for nucleotides, plus several choices for amino acids. The genetic algorithm (or GA, for short) search strategy used by GARLI is like other heuristic search strategies in that it cannot guarantee that the optimal tree will be found. Thus, as with all heuristic searches, it is a good idea to run GARLI several times (using different pseudorandom number seeds) to see if there is any variation in the estimated tree.
Today you will run GARLI on the cluster for a dataset with 50 taxa. This is not a particularly large problem, but then you only have an hour or so to get this done! Instead of each of us running GARLI several times, we will each run it once and compare notes at the end of the lab.
Preparing the GARLI control file
Like many programs, GARLI uses a control file to specify the settings it will use during a run. Most of the default settings are fine, but you will need to change a few of them before running GARLI.
Obtain a copy of the control file
The first step is to obtain a copy of the GARLI default control file. Go to the GARLI download page and download a version of GARLI appropriate for your platform (Mac or Windows). For now, the only reason you are downloading GARLI is to obtain a copy of the default control file. However, because GARLI is multithreaded, you may find that it is faster to run it on your laptop than on the cluster (assuming your laptop has a multi-core Intel processor). Running on the cluster has advantages, even if it is slower. For one, you don't have to dedicate your laptop to a GARLI run for several hours.
Once you have downloaded and unpacked GARLI on your computer, copy the garli.conf.nuc.defaultSettings to a file named simply garli.conf and open it in your text editor.
You will only need to change two lines. Change this line
datafname = zakonEtAl2006.11tax.nex
so that it looks like this instead
datafname = rbcl50.nex
Then change this line
ofprefix = nuc.GTRIG
so that it looks like this instead
ofprefix = 50taxa
The ofprefix is used by GARLI to begin the name of all output files. I usually use something different than the data file name here. That way, if you eventually want to delete all of the various files that GARLI creates, you can just say
rm -f 50taxa*
without wiping out your data file as well!
Save the garli.conf file when you have made these changes.
Log into the cluster
Log into the cluster using the command:
Go back to the Phylogenetics: Bioinformatics Cluster lab if you've forgotten some details.
Create a folder and a script for the run
Create a directory named garlirun inside your home directory and use your favorite file transfer method (scp, psftp, Fugu, FileZilla, etc.) to get garli.conf into that directory.
Now download the data file into the garlirun directory:
curl http://hydrodictyon.eeb.uconn.edu/eeb5349/rbcL50.nex > garlirun
Finally, create the script file you will hand to the qsub command to start the run. Use the pico editor to create a file named gogarli in your home directory with the following contents:
#$ -o junk.txt -j y cd $HOME/garlirun garli garli.conf
Submit the job
Here is the command to start the job:
You should issue this command from your home directory, or where ever you saved the gogarli file.
Check progress every few minutes using the qstat command. This run will take 15 or 20 minutes. If you get bored, you can cd into the garlirun directory and use this command to see the tail end of the log file that GARLI creates automatically:
The tail command is like the cat command except that it only shows you the last few lines of the file (which often is just what you need).