Welcome to the ninety fifth ever 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
[New Job Posting: Data Scientist II] We are hiring a Data Scientist II who will develop and maintain computational tools to support bioinformatics research at Fred Hutch, focusing on genomic, imaging, and laboratory-generated data. Responsibilities include creating automated data processing pipelines, building reproducible bioinformatics workflows, and developing interactive data visualizations for research collaboration. Candidates should have expertise in Python or R, experience with sequencing data analysis, and familiarity with cloud computing, workflow languages, and version control tools like Git.
[Training Opportunity: Openscapes @ Fred Hutch] The Openscapes Champions Cohort at Fred Hutch is a data science mentorship initiative in partnership with Openscapes, designed to foster collaborative and inclusive research practices. The Openscapes Champions Cohort Program supports scientific groups in modernizing data analysis, improving reproducibility, and adopting open science principles through a two-month remote program. Participants work in small cohorts, with team leads and members collaborating to develop shared workflows and sustainable practices. Applications for the Spring 2025 cohort (April 9–June 4) are open at the link above. Past participants have praised the program for enhancing reproducibility, fostering collaborative coding, and promoting open science methodologies.
Our Weekly Bookmarks Bar
[Blog Post: How to Use a Histogram as a Legend in ggplot2] Andrew Heiss explores using histogram-based legends in ggplot2 to improve the clarity of choropleth maps, particularly for visualizing U.S. county-level data. This post demonstrates how to replace traditional gradient legends with histograms, automate the process using
legendry, and enhance visualization with point-based maps and diverging color schemes. By centering unemployment rates around the Federal Reserve’s 4% target and using nested circle legends, the final visualization provides a more accurate and insightful representation of unemployment disparities.
As always you can contact us by replying directly to this email, you can contact the Data Science Lab at data@fredhutch.org, or 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 next week!
- The Fred Hutch Data Science Laboratory