Workshop Schedule
Day 1
Time | Topic | Instructor |
---|---|---|
9:30 - 10:10 | Workshop introduction | Radhika |
10:10 - 11:40 | Introduction to Shell | Meeta/Will |
11:40 - 12:00 | Overview of self-learning materials and homework submission | Will |
Before the next class:
- Please study the contents and work through all the code within the following lessons:
- Wildcards and shortcuts in Shell
- Examining and creating files
- Searching and redirection
- Shell scripts and variables in Shell
NOTE: To run through the code above, you will need to be logged into the FAS-RC cluster and working on a compute node (i.e. your command prompt should have the word
compute
in it).
- Complete the exercises:
- Each lesson above contain exercises; please go through each of them.
- Copy over your the answers for the exercises into a plain text file on your local computer, using Notepad++, TextWrangler or similar.
- Please do not copy all of the content from your Terminal, just the answers.
- Upload the text file to Dropbox the day before the next class.
Questions?
- If you get stuck due to an error while runnning code in the lesson, email us
- Post any conceptual questions that you would like to have reviewed in class here.
Day 2
Time | Topic | Instructor |
---|---|---|
09:30 - 10:45 | Self-learning lessons review | Radhika/Will |
10:45 - 12:00 | Loops and automation | Meeta |
Before the next class:
- Please study the contents and work through all the code within the following lessons:
NOTE: To run through the code above, you will need to be logged into the FAS-RC cluster and working on a compute node (i.e. your command prompt should have the word
compute
in it).
- Complete the exercises:
- Each lesson above contain exercises; please go through each of them.
- Copy over your the answers for the exercises into a plain text file on your local computer, using Notepad++, TextWrangler or similar.
- Please do not copy all of the content from your Terminal, just the answers.
- Upload the text file to Dropbox the day before the next class.
Questions?
- If you get stuck due to an error while runnning code in the lesson, email us
- Post any conceptual questions that you would like to have reviewed in class here.
Day 3
Time | Topic | Instructor |
---|---|---|
09:30 - 10:00 | Self-learning lessons review | All |
10:00 - 11:15 | Introduction to the FAS-RC cluster | Radhika |
11:15 - 11:45 | Exercise (answer key) | Will |
11:45 - 12:00 | Wrap up | Radhika |
Dataset
Introduction to Shell: Dataset
Answer keys
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:
- 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).