Workshop Schedule

Day 1

Time Topic Instructor
9:30 - 10:10 Workshop introduction Meeta
10:10 - 11:40 Introduction to Shell Radhika
11:40 - 12:00 Overview of self-learning materials and homework submission Jihe

Self Learning #1

Before you start with the self-learning portion of the workshop, please check that you are logged into O2 and are working on a compute node (i.e. your command prompt should have the word compute in it).

If you are not logged into O2 or are not on a compute node, please follow the steps below as appropriate before you start with the self-learning lessons:

  1. Log in using ssh rc_trainingXX@o2.hms.harvard.edu and enter your password (replace the “XX” in the username with the number you were assigned in class).
  2. Once you are on the login node, use srun --pty -p interactive -t 0-2:30 --mem 1G /bin/bash to get on a compute node.
  3. Proceed with the self learning once your command prompt has the word compute in it.
  4. If you log out between lessons (using the exit command twice), please follow points 1. and 2. above to log back in and get on a compute node when you restart with the self learning.

Assignment #1


Day 2

Time Topic Instructor
09:30 - 10:45 Self-learning lessons review All
10:45 - 12:00 Loops and automation Meeta

Self Learning #2

Assignment #2


Day 3

Time Topic Instructor
09:30 - 10:00 Self-learning lessons review All
10:00 - 11:00 Introduction to the O2 cluster Radhika
11:00 - 11:30 Exercise Meeta
11:30 - 11:45 Introduction to the O2 cluster - data storage Radhika
11:45 - 12:00 Wrap up Radhika

Dataset

Introduction to Shell: Dataset

Advanced bash commands

If you are interested in learning some more advanced tools for working on the command-line, we encourage you to walk-through the materials linked below:

Resources

Cheat sheets:

Online tutorials:

General help:


These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.