A workflow management system (WMS) is a piece of software that sets up, performs and monitors a defined sequence of computational tasks (i.e. “a workflow”). Snakemake is a WMS that was developed in the bioinformatics community, and as such it has a number of features that make it particularly well-suited for creating reproducible and scalable data analyses.

First of all the language you use to formulate your workflows is based on Python, which is a language with strong standing in academia. However, users are not required to know how to code in Python to work efficiently with Snakemake. Workflows can easily be scaled from your desktop to server, cluster, grid or cloud environments. This makes it possible to develop a workflow on your laptop, maybe using only a small subset of your data, and then run the real analysis on a cluster. Snakemake also has several features for defining the environment with which each task is carried out. This is important in bioinformatics, where workflows often involve running a large number of small third-party tools.

Snakemake is primarily intended to work on files (rather than for example streams, reading/writing from databases or passing variables in memory). This fits well with many fields of bioinformatics, notably next-generation sequencing, that often involve computationally expensive operations on large files. It’s also a good fit for a scientific research setting, where the exact specifications of the final workflow aren’t always known at the beginning of a project.

Lastly, a WMS is a very important tool for making your analyses reproducible. By keeping track of when each file was generated, and by which operation, it is possible to ensure that there is a consistent “paper trail” from raw data to final results. Snakemake also has features that allow you to package and distribute the workflow, and any files it involves, once it’s done.

If you want to read more, you can find several resources here:

The Snakemake documentation is available on readthedocs.
Here is another (quite in-depth) tutorial.
If you have questions, check out stack overflow.

This tutorial depends on files from the course GitHub repo. Take a look at the setup for instructions on how to set it up if you haven’t done so already, then open up a terminal and go to workshop-reproducible-research/tutorials/snakemake and activate your snakemake-env Conda environment.