Bioinformatics Training and Teaching with Galaxy
- Hans-Rudolf Hotz
- Alban Lermine
- Nikhil Joshi
- Björn Grüning
- Geir Kjetil Sandve
- Xiao Dong
- Morris Chukhman
- Warren Kaplan
- Madhavan Ganesh
- Graeme Grimes
- Ketaki Bhide
- Patra Volarath
- Erik Garrison
- Dave Clements
- Rama Sompallae
These notes are a rough first grouping of Dave Clements' notes from the breakout. Please feel free to update them.
- There is not a "teaching" instance of Galaxy anywhere. Options for training include using your own instance, using main, or using a cloud instance.
- Weeklong course at UC Davis with everyone doing their own bioinformatics on the cloud. This is very inexpensive.
- having 40 people on same instance can be a problem
What Participants Have Been Doing
- Weeklong course on bioinformatics.
- Two back to back courses. Only used UCSC encode and Galaxy. RNA-Seq analysis.
- Perl for bioinformatics.
- Use Galaxy for training, bioinformatics school
- Don't use Galaxy internally at the bioinformatics core, but do use it for training.
- Started teaching with command line and that was a disaster.
- Use Galaxy to teach students, some of whom have not used a computer before. Galaxy might be too complicated for that group.
Goals for Training
- Want to be able to teach biologists enough so that they can do the analysis, but also to have them learn how to do in depth analysis.
- To learn programming
- Galaxy as a visual programming language.
- Don't have to teach R or Perl, but the ideas: transform the ides
- Make bioinformatics training a part of medical education.
- Teach people to do their own analysis.
- Not enough time for training. Just do intro to bioinformatics using Galaxy
- Problem with teaching is that participants forget it after a month, if they don't use it frequently after the training.
- Teaching R is an order of magnitude harder to teach than perl
- Do you teach the details or high level?
- Researchers who have specific needs.
- You have students who you want to teach basic understanding too
- We also need to train the biologists and chemists to use the tools, but too understand the outputs.
- Some past bioinformatics training focused on statistics to the point of alienating biologists
- Trainers can't know every detail of every tool
- How do you communicate the complexity of analysis and tools?
- Can ask researchers "what do you want to assume?" That's a lot work.
- Asking "which statistical test do you want to use" is not a question that many researchers can answer meaningfully.
- Biologists are really good at following protocols, as long as they are at the bench. Following recipes on computers is not the same thing.
- Researchers that just want the data analyzed without understanding analysis. Some would prefer to have an analysis blackbox, with a red button that says "analyze."
- The interface for files in Galaxy is confusing for users.
- How do you have a meaningful example that runs fast.
- Number of tools is daunting
- Bioinformatics courses are not as good as many other courses
- Textbooks are not as good
- Field is developing so fast; no chance to standardize
- End up with Bioinformatics for dummies courses
- Jeremy's parameter walking can make it clear that they can get different results.
- Flip side is this can be used to get the results they want.
- Demonstrate how sensitive things are.
- Improve interface for history / files in Galaxy
- tie together files that are produced as a chunk.
- Change it to be more hierarchical. Have folders. Too many files, e.g. cufflinks get 11 files.
- Get Multiple views.
- Does Galaxy have access to Human Computer Interaction folks?
- Struggling with tools can get the point across that this is inherently difficult
- Galaxy is about the making the simple things easy to do, so you can get to the science.
- Include a "Hey this is important!" notice on complex tools.
- What students really like: Show them and RNA-Seq un-replicated, and then we contrive a grand challenge and do some analysis to gain insight into that. Split people up into groups and have them tackle it. They like that a lot.
- hands-on workshops may be overrated. Maybe speak for an hour, and then have participants go off for a few days.
- Take a high-profile paper and reproduce the results from a paper. That's going to be motivating.
- Set up a catalog of teaching material
- Want to be able to share material
- slide sharing would be helpful
- Teach good Galaxy practices
- Always rename your output files
Plan of Action
We did not discuss a plan of action at the breakout, but we will here.
More to come ...