Workshop Schedule

Day 1

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.

• Wildcards and shortcuts in Shell
• Examining and creating files
• Searching and redirection
• Shell scripts and variables in Shell

Assignment #1

• All exercise questions from the self-learning lessons have been put together in a text file (download for local access).
  • The text file can be opened with any text editor application (i.e. Notepad++, TextWrangler) on your local computer
• Add your solutions to the exercises in the downloaded .txt file and upload the saved text file to Dropbox day before the next class.
• Email us about questions regarding the homework that you need answered before the next class.
• Post questions that you would like to have reviewed in class here.
• Answer Key

Day 2

Self Learning #2

• Permissions and Environment Variables
• Introduction to High-performance computing

Assignment #2

• All exercise questions from the self-learning lessons have been put together in a text file (download for local access).
  • The text file can be opened with any text editor application (i.e. Notepad++, TextWrangler) on your local computer
• Add your solutions to the exercises in the downloaded .txt file and upload the saved text file to Dropbox day before the next class.
• Email us about questions regarding the homework that you need answered before the next class.
• Post questions that you would like to have reviewed in class here.
• Answer key

Day 3

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:

• More fun with bash commands
• Advanced bash commands (aliases, copying files, and symlinks)

Resources

Cheat sheets:

• http://fosswire.com/post/2007/08/unixlinux-command-cheat-sheet/
• https://github.com/swcarpentry/boot-camps/blob/master/shell/shell_cheatsheet.md
• tldr_ : Simplified version of the man pages (online and searchable)

Online tutorials:

• Explain Shell
• Introduction to the Command Line for Genomics
• BASH Programming - Introduction HOW-TO
• Bioinformatics from the Command Line

General help:

• Google it! - if you don’t know how to do something, try Googling it, other people have probably had the same question.
• Learn by doing! There’s no real other way to learn this than by trying it out.
  • Use vim on your laptop
  • Move around the directory structure on your laptop using the Terminal/Shell counts
  • Open folders and files using the command open
  • Automate something you don’t really need to automate
• Use man bash to get more information about bash (bourne-again shell)

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.

• Some materials used in these lessons were derived from work that is Copyright © Data Carpentry (http://datacarpentry.org/). All Data Carpentry instructional material is made available under the Creative Commons Attribution license (CC BY 4.0).