Hello! Today we'll be going through some hands-on activities to help you get familiar with how PhyloAcc is run and how it can be used to identify genomic elements that have experienced accelerated evolution.

This course will have 2 parts: one where we are on the server and running commands and another where we download some pre-run data to analyze with R.

Most of our work in the first part of the course will be done as bash commands typed in the Terminal. Throughout this walkthrough, commands will be presented as follows:

this is an example command

Following each command will be a table that goes through and explains each part of the command explicitly:

The goal of providing these tables is to break-down some of the 'black box' that command line tools can sometimes feel like. Hopefully this is helpful. If not, feel free to skip over these tables when you see them!

Here is some made up output.
Looking at your data is very important!
You can catch problems before you use the data in later analyses.

If you want to follow along by running the commands, the first thing you should do if you haven't done so is to connect to Cannon, our cluster, such that you can run commands from a terminal. There are different ways to do this, but the easiest thing would to just open up Terminal (on Mac) or PowerShell (on Windows) and run the following command:

ssh [your user name]@login.rc.fas.harvard.edu

This should prompt you for your password and 2-factor authentication code, at which point you should see something like this:

Figure 1.1: Cannon right after logging in.

In addition to logging on to the server as above, we're also going to start an interactive session on one of the compute nodes so that we don't bog down any of the login nodes trying to run PhyloAcc:

salloc -p test --mem 12g -c 8 -t 0-02:00

Once logged in, we'll load the PhyloAcc package. I've pre-made a conda environment with PhyloAcc installed in it. To load it, first load Anaconda:

module load Anaconda3

Next, load my pre-made environment

source activate /n/holylfs05/LABS/informatics/Everyone/phyloacc-data/workshop-20221027/env/phyloacc-workshop

Then, let's make sure everything loaded correctly by running a check:

phyloacc.py --depcheck

When you do this, you should hopefully see something like this, with both binaries reporting PASSED statuses:

# --depcheck set: CHECKING DEPENDENCY PATHS AND EXITING.

   PROGRAM          PATH                STATUS
   -------------------------------------------
   phyloacc         PhyloAcc-ST         PASSED
   phyloacc-gt      PhyloAcc-GT         PASSED

# All dependencies PASSED.

If you don't see this, or one or both of the checks failed, please let me know.

To keep things organized, let's make a new folder specifically for this workshop. First let's make sure you're in your home directory:

cd ~

And this will create a folder in your home directory, but feel free to do it anywhere you like.

mkdir phyloacc-workshop

Finally let's enter our new directory so any files we create will be put in it:

cd phyloacc-workshop

Now, let's move on to an intro to our data