The rest of this wiki provides general guidelines and approaches to working with data at Fred Hutch. This reference section includes information on where to obtain training, as well as specific step-by-step tutorials for accomplishing tasks with Hutch resources.
There are many opportunities for training (courses and tutorials) and connecting with coding communities. The Fred Hutch Bioinformatics and Data Science Cooperative (The Coop) and fredhutch.io offer events and meeting groups. Additional opportunities are available elsewhere in Seattle (at UW and through Meetup.com) and online.
This FAQ-style page includes answers to questions like “How do I get started learning to code?” and “What language should I learn first?”
The Resource Library contains both links to GitHub repositories containing templates for coding projects and example code, as well as tutorials and demonstrations for accomplishing tasks with Hutch data science resources.
Scientific Computing sends email updates to their list of users about changes to software and hardware. Important announcements are also archived here.
Templates and Examples GitHub Repositories
There are a handful of useful resources emerging alongside this Wiki page that are sources of assistance that might be relevant to your work.
slurm-examples GitHub Repository
SciComp is reviewing emerging contributions of example starter scripts that focus on connecting your work to computing resources supported by SciComp. You can find that repository here.
wiki-code-examples GitHub Repository
Fredhutch.io is providing and reviewing example code for various data wrangling and analysis purposes. That emerging resource can be found here.
wiki-templates GitHub Repository
The Fred Hutch
wiki-templates repository aims to describe the minimum file requirements for several project types. Each project folder serves as a template and guide for following best coding practices and is an evolving resource meant to help people get started. You can find that repository here.
Updated: October 22, 2019Edit this Page via GitHub Comment by Filing an Issue Have Questions? Ask them here.