Fred Hutch offers a variety of educational resources on aspects of bioinformatics, analytics, and working with data. Here you can find the opportunties for training and help offered through Fred Hutch as well as access a resource library of external online educational content.
While we are currently working to add staffing support for instructor-led training activities, we hope to offer targeted workshops in the near future.
Keep an eye out for:
- Journal clubs to bring together people with shared interests in a particular method or technology to discuss current, high-impact papers.
- Workshops that offer training specific to Fred Hutch infrastructure such as how to effectively use the SLURM cluster or access and use AWS.
Instructor-led opportunties are in the planning stage and pending staff support.
Self-directed learning through Fred Hutch
For those who aren’t able to attend in-person courses we have a range of standalone resources to help guide their self-directed learning.
- Fredhutch.io is an initiative to facilitate education about and promote access to computational resources at Fred Hutch. Those interested in learning core computational skills like R and Python can work through this content at their own pace.
Bioinformatics and Genomics Resource Library is a curated list of external resources related to bioinformatics and genomics including peer reviewed papers, blog posts, and video tutorials.
- The Scientific Computing Resource Library includes tutorials of how to perform common computational tasks using software available at Fred Hutch. Below we’ve highlighted a few popular links, but be sure to check out the page to see all the tutorials available.
- Code templates and examples have been developed for those who are interested in implementing methods from the Scientific Computing Resource Library on their own data following best practices for reproducibility. Code templates are provided for setting up your own analyses, as well as addtional examples of executable code that can be tailored to suit your own needs.
Due to the nature of self-directed learning there is no instructor immediately available to answer questions or troubleshoot. Please bring questions to the relevant office hours (listed below) or to the FH-BCR Slack.
Office hours are available for many of the shared resources on campus. Bring your questions and get answers! Currently most office hours are hosted on MS Teams. You can find links to office hours and get regular reminders by joining the Fred Hutch Bioinformatics and Computational Research (FH-BCR) community Slack workspace.
- Hutch Data Core: Staff are available to assist researchers in getting started with bioinformatics and orienting staff to resources for improving their coding, including troubleshooting application of code to research questions.
- Hosted Every Tuesday from 9:00 to noon, staffed by Lauren Wolfe
- Scientific Computing - General: Scientific Computing (SciComp) manages basic account access for research computing resources, including data storage and shared computational cluster use. Staff are available to answer questions related to access and usage of Hutch resources for computational research.
- Hosted every Wednesday from 10:00 to noon, staffed by Ben McGough
- Scientific Computing - Cloud/Next Gen: In addition to general consulting (see above), Scientific Computing (SciComp) supports researchers interested in emerging technologies like next generation sequencing and cloud computing. Staff are available to answer questions about getting started building analytical pipelines in the cloud, and generally making computation more scalable and reproducible.
- Hosted every Tuesday from 3:00 to 4:30, staffed by Dan Tenenbaum
- Ethics and Compliance: Staff from the Center Information Technology (CIT) Compliance Office with expertise in information security are available to answer questions related to secure data management and resources at the Hutch for security compliance.
- Hosted every Wednesday from 10:00 to noon, staffed by Susan Glick
We are working to formalize office hours for many of the Shared Resources offered through Fred Hutch. Please keep an eye on this page for updates!
- Genomics & Bioinformatics: Staff from the Genomics and Bioinformatics Shared Resource are available to answer questions related to the generation and analysis of genomic data from DNA array, genetic analysis and high-throughput screening methods.
- Bioinformatics staffed by Matt Fitzgibbon.
- Genomics staffed by Cassie Sather.
- Image Analysis: Staff with expertise in image analysis are available to answer questions.
- Staffed by Julien Dubrulle.
- Flow Cytometry: Staff from the Flow Cytometry Shared Resource are available to answer questions from aiding scientists on panel design, and marker and color choice to data analysis and troubleshooting.
- Staffed by Andrew Berger.
- Proteomics & Metabolomics: Staff from the Proteomics and Metabolomics Shared Resource are available to answer questions related to sample preparation, sample separation, data collection and data analysis.
- Staffed by Phil Gafken.
- Cellular Imaging: Staff from the Cellular Imaging Shared Resource with expertise in advanced microscopy incluidng light microscopy and electron microscopy are available to answer questions.
- Staffed by Peng Guo.
- Cryo-EM: Staff from the Cryo-EM Shared Resource are available to answer questions realted to sample preperation, data collection, and data processing.
- Staffed by Caleigh Azumaya.
Office hours can also be found on the Centernet Calendar.
Due to COVID-19 all office hours are currently hosted through MS Teams.
Resources In Seattle
- UW Biostatistics Summer Institutes offer yearly intensive courses over the summers on a wide variety of topics.
- Meetup hosts various coding groups that meet regularly to share skills and provide networking opportunities. RLadies Seattle and Seattle UseR both include leaders from Fred Hutch.
External Resources On the Web
These resources are organized in a lecture type format as slides, screencasts, and video. Most are work-at-your-own-pace, but some may be linked to a course calander.
- MCB517A: Tools for Computational Biology: A graduate-level course taught for UW by Fred Hutch CompBio faculty. This links to a GitHub repository that includes all lectures and homework.
- edX: Offers a collection of courses for Data Analysis and Statistics and Bioinformatics
- Rafael Irizarry of Dana Farber has online programs available through edX:
- Generally speaking, edX courses are all free to audit for a limited period of time. Unlimited access and the ability to earn a course Certificate will require payment
- Coursera: Offers a collection of courses for Data Science and Bioinformatics
- R Programming: A beginner-level program has five mini-courses. It takes about 4 months to complete.
- Statistics with R: A beginner-level program with five mini-courses. It takes about 7 months to complete.
- Genomic Data Science: An intermediate-level program for those who are already aquainted with R. It has eight mini-courses. It takes about 6 months to complete.
- Python Programming: An intermediate-level program that takes about 4 months to complete.
- Coursera offers a 7-day free trial, and is a paid subscription service after
- Udacity: Offers a collection of courses for Data Science
- Udacity is a paid subscription service
- Currently offering one month free for their Nanodegree programs.
- Udemy: Offers a collection of courses for Data Science
- Udemy offers courses at various price points.
- Keep an eye out for sales which happen regularly and can drastically reduce the cost.
- CognitiveClass.ai Offers a collection of courses for data science, AI, and cloud computing.
- All courses are free
- The Open Source Data Science Masters: An open-source curriculum for learning data science. This is a mixed media course made up of videos, books, and slides.
- Some content is free, some is paid
- CalTech Learning from Data
- A free YouTube series
- Jesse Showalter - Command Line Basics (<15min video)
- Corey Schafer - Git Tutorial for Beginners: Command-Line Fundamentals (30 min video)
- Webinars from R studio (30 min - 1 hr / video)
- Getting Started With R Markdown
[Easy Ways to Collect Different Types of Data from the Web with R Part 1](https://www.rstudio.com/resources/webinars/part-1-easy-ways-to-collect-different-types-of-data-from-the-web-with-r/)
[Easy Ways to Collect Different Types of Data from the Web with R Part 2](https://www.rstudio.com/resources/webinars/part-2-easy-ways-to-collect-different-types-of-data-from-the-web-with-r/)
- Debugging Techniques in RStudio
- A Gentle Introduction to Tidy Statistics in R
- Managing Packages for Open Source Data Science
- Tidyverse Visualization and Manipulation Basics
- Introduction to Shiny
- Corey Schafer - Python beginners series (15 - 30 min / video)
- Install and Setup for Mac and Windows
- Strings - Working with Textual Data
- Integers and Floats - Working with Numeric Data
- Lists, Tuples, and Sets
- Dictionaries - Working with Key-Value Pairs
- Conditionals and Booleans
- Loops and Iterations
- Import Modules and Exploring The Standard Library
See Corey’s YouTube Channel for more tutorials including intermediate and advanced Python topics
- Dataschool.io - Best Practices with Pandas (2 hr)
Core Coding Concepts
- Data Structures and Algorithms Series - Coding Dojo (15 - 30 min / video)
Interactive Coding Platforms
These resources offer classes that are work-at-your-own-pace with a major focus on hands-on problem-sets and projects.
- DataQuest: A subscription service that offers programs and courses focused on data anlysis and engineering in Python and R.
- Tiered payment system with basic and premium plans
- CodeAcademy: A subscription service that offers coding programs and courses in many different languages.
- Tiered payment system with limited content available for free
O’Reilly books available through Seattle Public Library
Please reach out to the Hutch Data Core by sending an email to
hutchdatacore with questions, comments, or suggestions related to training!
Updated: October 27, 2021Edit this Page via GitHub Comment by Filing an Issue Have Questions? Ask them here.