This is a derivative of https://datacarpentry.org/wrangling-genomics/
The main changes are:
- The inclusion of the Introduction to Git from Software Carpentry - this content too has been modified
- Making the content specific to running on NeSI, rather than AWS
A lot of genomics analysis is done using command-line tools for three reasons:
1) you will often be working with a large number of files, and working through the command-line rather than
through a graphical user interface (GUI) allows you to automate repetitive tasks,
2) you will often need more compute power than is available on your personal computer, and
connecting to and interacting with remote computers requires a command-line interface, and
3) you will often need to customize your analyses, and command-line tools often enable more
customization than the corresponding GUI tools (if in fact a GUI tool even exists).
In a previous lesson, you learned how to use the bash shell to interact with your computer through a command line interface. In this
lesson, you will be applying this new knowledge to carry out a common genomics workflow - identifying variants among sequencing samples
taken from multiple individuals within a population. We will be starting with a set of sequenced reads (.fastq files), performing
some quality control steps, aligning those reads to a reference genome, and ending by identifying and visualizing variations among these
samples.
As you progress through this lesson, keep in mind that, even if you aren’t going to be doing this same workflow in your research, you will be learning some very important lessons about using command-line bioinformatic tools. What you learn here will enable you to use a variety of bioinformatic tools with confidence and greatly enhance your research efficiency and productivity.
Prerequisites
This lesson assumes a working understanding of the bash shell. If you haven’t already completed the Shell Genomics lesson, and aren’t familiar with the bash shell, please review those materials before starting this lesson.
This lesson also assumes some familiarity with biological concepts, including the structure of DNA, nucleotide abbreviations, and the concept of genomic variation within a population.
This lesson uses data hosted on NeSI. Workshop participants will be given information on how to log-in to the NeSI cluster during the workshop. Learners using these materials for self-directed study will need to set up their own project allocation from NeSI. Information on setting up and accessing the required data is provided on the Genomics Workshop setup page.