Installing LocalColabFold Locally

If you would like to maintain control over when LocalColabFold is updated, you may choose to install it to a local folder under your direct control. We outline instructions on how to do so below.

Installing LocalColabFold

First, begin an interactive session (https://harvardmed.atlassian.net/wiki/spaces/O2/pages/1586793632/Using+Slurm+Basic#Interactive-Sessions ) and load the conda module (preferably with nothing else loaded, run module purge to remove all active modules from your current environment):

$ module load miniconda3/4.10.3

Then, cd to a location where you would like to clone the LocalColabFold repository (https://github.com/YoshitakaMo/localcolabfold ), then do so:

$ git clone https://github.com/YoshitakaMo/localcolabfold.git

This command will create a folder in your working directory called localcolabfold. cd into this directory. Then, if you ls this location, you should see the files that are in the repository view on GitHub accessible via your terminal in your local folder that was just created. We are interested in the install_colabbatch_linux.sh file. Remember the path to this file (we will refer to this path as /path/to/install_colabbatch_linux.sh from now on; replace it with your own path). Now, cd to a location where you would like the environment to live, then invoke this script:

$ cd /path/to/desired/location $ sh /path/to/install_colabbatch_linux.sh

This should create a directory at /path/to/desired/location called colabfold_batch. Wait for the installation to finish.

Keeping Your LocalColabFold Installation Updated

The main reason you are probably maintaining a personal LocalColabFold installation is likely because you would like to use the newest features as they are implemented into ColabFold, without waiting for the module to be updated erratically (or perhaps not at all depending on stability). To keep your installation updated, return to the location where you cloned the repository (recall that it was called localcolabfold when it was created via git clone:

$ cd /path/to/localcolabfold

Now that you’re here, you’ll want to make sure that these scripts are updated:

$ git pull

Now, you’ll want to run the update_linux.sh script, and pass the path to your environment as an argument:

$ sh update_linux.sh /path/to/desired/location/colabfold_batch

After this is complete, you should have the newest version of ColabFold baked into your LocalColabFold installation.

Executing LocalColabFold Locally

Now that you have installed LocalColabFold locally, there is one more hurdle to using this installation.

First, make sure the bin subdirectory is added to your PATH variable:

$ export PATH=/path/to/desired/location/colabfold_batch/bin:$PATH

If you prefer, you can paste this line into your ~/.bashrc file instead so that it is automatically set up each time you log in to O2.

In order to leverage GPU resources, you will need to load a CUDA module, which in turn requires you to load a GCC module:

$ module load gcc/9.2.0 cuda/11.2

Via internal testing, Research Computing has discovered that even though install_colabbatch_linux.sh installs a local copy of (GCC and) CUDA, it is unable to leverage these resources, and we were unable to provide access to these local copies. The present workaround is to use the O2 modules in their place as above.