01 - Introduction
Table of contents
My background
- Bioinformatician at the Institute of Environmental Science and Research (ESR)
- Analyse human genomic data
- MSc - population genetics
Benefits of workflow languages
- Reproducibility
- Automation
- Portability
- Scalability
- Interpretability
A good paper on Scalable Workflows and Reproducible Data Analysis for Genomics - although genomics focussed, it covers a lot of the concepts we will touch on in this workshop
Benefits of Snakemake
- Based in the popular (and widely used) programming language, Python
- Great documentation, actively maintained (but so are the other workflow languages mentioned below)
- Easier to learn (particularly if you’re familiar with python)
- Flexible
See what other people think:
- https://www.biostars.org/p/345998/
- https://www.reddit.com/r/bioinformatics/comments/f3rxel/snakemake_vs_nextflow/
- https://www.biostars.org/p/258436/
Other workflow languages
Choose your favourite flavour of workflow language!
- Common Workflow Language (CWL)
- Nextflow
- Workflow Description Language (WDL)
- Guix Workflow Language (GWL)
The real point is to use a workflow language (where applicable) and just use the flavour you like!
This workshop
This workshop is designed with someone who had some familiarity with the command line. However, I’ve tried to make it as accessible as possible to anyone who want to learn Snakemake.
Throughout this workshop, I’ll be indicating the code to remove and the code to insert (relative to the previous step) with the following:
- Remove this line of code
+ Add this line of code
However, the actual + and - symbols should not be included in your own code