Thinking Science with Statistics and Computers¶

Abstract

I’m a scientist whose career has focused on developing statistical and computational methods for genetics and genomics. Here, I share advice and lessons learned from conducting research and from teaching others how to do it. I also provide reports on experiments related to my open-source software.

May 20, 2026
in bioinformatics
10 min read

The parser shootout 🔫

Bioinformatics data processing remains dominated by plain text formats. In this post, I contrast the performance of the popular biopython, cogent3, and scikit-bio packages for reading three sequence file formats and two genome annotation formats. Despite how simple these tasks might seem, you'll see there's a lot of variation in performance! The takeaway message is that cogent3 is nearly always faster for parsing these basic file formats, while biopython typically uses less RAM.

Mar 1, 2022
in computational science
10 min read

Setting up your computer for computational research

How much impact can a computer setup possibly have? Some choices can make your daily life as a computational scientist a lot happier. Conversely, other choices can make you curse yourself. If it sounds like I'm talking from experience, you're correct -- 20+ years worth.

Feb 25, 2022
in computational science
9 min read

So you're starting a research project, where do you begin?

This post is intended for anyone starting out in research and development with a computational bent, whether in a science (e.g. computational biology) or engineering context. In particular, it is focussed on the research process that leads to new tools and analysis methods.