Summary and Setup
Command line interface (CLI) and graphic user interface (GUI) are different ways of interacting with a computer’s operating system. They have different pros and cons. Most people are familiar with the GUI as it is the default interface for most software, particularly on Windows and Mac OS. When using the GUI, you see and interact with visual representations of files, folders, applications, and most other functions of your computer. When using the CLI, you work largely with text representations of software, files, folders, input and output. The shell is a program that allows you to control your computer by typing instructions on the CLI with a keyboard.
There are several reasons to learn how to use the CLI:
- For most bioinformatics tools, there are no graphical interfaces. If you want to work in metagenomics or genomics, you’re going to need to use the CLI/ shell.
- The shell gives you power. The command line allows you to work more efficiently. Tasks that are repetitive (e.g. renaming hundreds of files) can be automated. Tasks that are tedious (e.g. testing a range of input parameters) can be simplified.
- To use remote computers or cloud computing, you often need to use the shell.
Getting Started
This lesson assumes no prior experience with the tools covered in the workshop. However, learners are expected to have some familiarity with biological concepts, including the concept of genomic variation within a population. Participants should bring their laptops and plan to participate actively.
This lesson is part of a workshop that uses data hosted on an Amazon Machine Instance (AMI). Workshop participants will be given information on how to log-in to the AMI during the workshop. Learners using these materials for self-directed study will need to set up their own AMI. Information on setting up an AMI and accessing the required data is provided on the Genomics Workshop setup page.
For Instructors
If you are teaching this lesson in a workshop, please see the Instructor notes.
This workshop is designed to be run on pre-imaged Amazon Web Services (AWS) instances. For information about how to use the workshop materials, see the setup instructions on the main workshop page.