The Holmes and Huber labs collaborate on developing statistical tools for large multi-layer data analyses, for integrating large, heterogeneous biological data, and for finding applications in molecular medicine. They aim to deliver tools that are easy to use by domain-scientists to analyze their own data – for instance by providing the tools in the form of R / Bioconductor packages.
Together they want to help the next generation of biologists understand the “black box” of statistics by training them in quantitative statistical methods. They have written a textbook (Modern Statistics for Modern Biology) and together, they teach a summer course (Stats 366 – Bios 221) at Stanford. They keep further developing these materials, to take up new scientific developments (e.g. new data types), new methods, or new statistical or computational ideas.