Autumn 2020 updates from the Coop Team

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Written by: The Coop Team - Fred Hutch Bioinformatics & Data Science Cooperative

The Coop is a community-centered organization, and the Coop Team feels strongly about sharing our progress and plans with out most important stakeholders: researchers and staff involved in data-intensive and computational work at Fred Hutch!

This post is the first in a regularly occurring series in which we plan to share our progress from the previous three months (i.e., calendar quarter), as well as what we have planned over the next quarter. We know how hard it can be to feel connected to and knowledgeable about what is happening in the community, and we hope this type of transparency will help you plan, network, and keep working on amazing, cutting-edge science!

Summer 2020 (July to September) progress report

We began our last quarter continuing to adjust to our organizational placement in the Interdisciplinary Science Adminstration (ISA) Core Team, which allowed us to maintain connections with other members of Shared Resources and the Integrated Research Centers (IRCs). However, the departure of a few important team members required the two remaining staff assigned to training and community (Kate Hertweck and Lauren Wolfe) to inventory and reassess all supported projects. When combined with logistical challenges associated with working remotely, much of this quarter was dedicated to connecting with collaborating groups on campus, including committees sponsored by CIT related to data storage and data governance, as well as leadership and advisory boards for various data-intensive research groups at Fred Hutch.

Sharing information is one of the key services we perform at the Coop, so revising our communication plan was one of the primary projects for this quarter. We took the summer off from publishing the newsletter, and have also decided to transition from a monthly to quarterly newsletter publication cycle. This makes sense because we have fewer events requiring advertisement, and also allows us to commit more time to posting community highlights and announcements via the Coop Blog. We continue to administer communications via the Coop Communities Slack, The Coop in MS Teams, and weekly office hours (Tuesday from 9 am to noon in MS Teams!). Finally, we continually develop and edit content for the Biomedical Data Science Wiki, including reference pages about computational resources, tutorials about common computing tasks, and example code and templates.

Given demand for instructor-led classes seemed to be decreasing, we decided to focus our efforts on improving training materials as publicly accessible for anyone to use for self-directed learning at any point. We are grateful for community members who tested the Introduction to R and Introduction to Python materials to ensure an instructor was not required to work through all exercises. We are continuing to revise existing courses, like Data for Data Science and the machine learning series, so they are also able to perform with self-directed learning. We were also pleased to work with three teaching assistants from the Molecular and Cellular Biology (MCB) program at UW to assess and create new course material, which will be included in upcoming course releases.

Finally, this quarter we are pleased to have published our Coop Community Values, which we plan to use as the framework for our future planning.

Autumn 2020 (October to December) planned projects

Our first big announcement for this quarter: we are pleased to announce that the Coop Team has formally joined Scientific Computing! We will still be focusing our efforts on community and training, but are excited to leverage closer ties with the folks developing and supporting computing infrastructure to maximize the impact our work can have on scientific research. We are grateful to Sheila Charles in ISA for her support during our transition period in ISA, and look forward to continuing to build relationships with her group.

Our efforts to connect with other groups involved in data-intensive research will pay off this quarter, as we continue improving our communication strategy and aligning more closely with other Shared Resources. We are working with SciComp to develop a strategy to onboard researchers to data-intensive research, whether they are new to computing or new to the Hutch.

From a training perspective, the content for the next collection of courses to develop has finally coalesced, including:

  • Concepts in Data Visualization, with corresponding intermediate R and Python courses
  • Introduction to Unix Command Line, a pre-requisite for remote high-performance computing classes (HPC: rhino and gizmo, HPC: Cloud computing with AWS)
  • Genomics, a series of modular short courses about selecting bioinformatics methods, running command line programs, and reproducibly building pipleines

Additionally, to support the application of technical skills following courses, we are developing practice exercises and projects so researchers can maintain and improve their skills in preparation for analyzing their own data. We are grateful for the willingness of individual researchers and labs to work with us in designing our training materials!

We’ve certainly got our hands full with these goals, but are always happy for feedback from our community! Drop us a message at coophelp, or reach out on Slack or MS Teams to let us know if you think there’s anything we’re missing.