🐦⬛ Je Ne Sais Quoi
I know it when I see it
Welcome to the one hundred and fifteenth issue of Monday Morning Data Science from the Fred Hutch Data Science Laboratory. We are excited to show you what we have been working on (Fresh from the Lab), plus links that we think you would be interested in (Our Weekly Bookmarks Bar). Part of the purpose of this newsletter is to start conversations, so if you have a question or there is something you would like to share with us please let us know by responding directly to this email.
Fresh from the Lab
[Workshop: Making Code Ready for Publication] DaSL Director of Education Ted Laderas explains why making analysis code publication-ready is important for reproducibility, transparency, and future reuse, with an emphasis on documenting projects so others (and your future self) can rerun the work. This talk outlines practical steps such as organizing projects with scripts, data, and a README, using lockfiles to pin package versions, and sharing the project through repositories (e.g., GitHub) with tools like Binder or Docker to recreate the computational environment.
Our Weekly Bookmarks Bar
[Blog Post: A Few Claude Skills for R Users] Isabella Velásquez introduces Claude Skills, which are modular instructions that extend the capabilities of the AI assistant Claude. She highlights community-created skills that help R users generate modern, tidyverse-style code, work with Quarto and Shiny, manage package releases, and follow best practices. She also explains how these skills differ from project-wide configuration files and shows how users can install or create their own skills to customize AI-assisted R development workflows.
[Blog Post: Setting up ast-grep with R Support] Emil Hvitfeldt explains how to enhance AI-assisted coding with CLI tools by integrating syntax-aware code search using ast-grep, which can find patterns in code (like specific function structures or argument usage) that are difficult to detect with regular expressions. It shows how to add R language support via tree-sitter and configure it so Claude Code can automatically use the tool to analyze and search R code more effectively.
As always you can contact us by replying directly to this email, or if you work within the Fred Hutch/University of Washington/Seattle Children’s Cancer Consortium you are welcome to join us on the Fred Hutch Data Slack Workspace. For more information about the Fred Hutch Data Science Lab, visit our website: https://hutchdatascience.org/. See you in two weeks!
- The Fred Hutch Data Science Laboratory