Announcing the scikit-bio cookbook “recipe-of-the-week” series

scikit-bio is a library for building bioinformatics tools and workflows in Python. It’s already a core dependency of QIIME, is extensively used in An Introduction to Applied Bioinformatics, and was the subject of my talk at SciPy 2014 (video) this past July. One of our focuses with scikit-bio is to make its functionality very accessible by providing amazing documentation. We’ve largely done that through our numpydoc-compliant API documents so far – see here, here and here for some good examples.

The scikit-bio cookbook: delicious and nutritious bioinformatics recipes

We’re now interested in expanding our documentation to illustrate how to build more complex bioinformatics workflows using scikit-bio. Toward that end we have created the IPython Notebook-based scikit-bio cookbook.

As of now, we have five recipes in the cookbook:

Over the next 10 weeks, we’re going to expand the contents of the scikit-bio cookbook through a recipe of the week series where we’ll post one new recipe per week. As we create new recipes, we’ll tweet about them with the #skbio hashtag, so follow that (or me) to get those updates.

We want your recipe requests!

Since a lot of the developers of scikit-bio come from a microbial ecology background, several of the existing recipes are focused on tasks that frequently need to be achieved in amplicon (e.g., 16S) surveys. So far we’ve been coding up the recipes that are most relevant to us, but scikit-bio isn’t just a tool for microbial ecology.

If you have a bioinformatics workflow in mind that you’d like to see as a scikit-bio recipe, please post to the scikit-bio-cookbook issue tracker with details on that request. We’ll watch those issues to get ideas about what recipes to add, and if someone posts a recipe idea that you’d also like to see, respond to that issue with a “+1” to vote that recipe up.

We’re also very interested in recipe contributions from our users, so if you’re interested in contributing a recipe, we’d love to hear from you. In that case, it’s also probably best to post an issue with your idea and note that you’d like to work on it – that will help us to avoid duplicated effort.

We hope that you’ll enjoy scikit-bio and the scikit-bio cookbook.

-Greg (on behalf of the scikit-bio development team)



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Greg Caporaso

Greg Caporaso is a professor of bioinformatics at Northern Arizona University.