We would rather you could do the routine parts yourself.

More than 30 hands-on trainings a year, aimed at making complex methods accessible, turning computational technique into biological insight, and helping investigators apply the right statistical approach to a real problem rather than a textbook one.

Topics span statistical analysis of bulk and single-cell data, open-source tools and pipelines for genomics, transcriptomics, and epigenomics, R, UNIX, high-performance computing, machine learning pipelines, and AI best practices. We also run sessions on publishing your code: putting work on GitHub, collaborating with colleagues, releasing a function or library, and building a project website.

Most workshops are free and come with a certificate of attendance. We can tailor a remote, hybrid, or on-site session to a single lab or a company.

We have been part of the PUMAS, SEP, NexGeneGirls, and CCSF education programs since 2021, and we take interns. Both are worth asking about.