Velsera is deeply committed to enabling precision medicine not only through accelerating discoveries but also through training the next generation of scientists. With the rapid increase of multi-omics data availability and the increasing need for analysis of the publicly available resources, it is of paramount importance that young scientists include this knowledge in their research and learn how to make the most of it.
Many multi-omics and bioinformatics analyses that once were the province of programmers are now indispensable for everyday clinical care. This rapid shift has been accompanied by an increase in student interest, especially college students eager to enter the health care field who recognize the value of bioinformatic skills, and how to apply it for discovery. In this blog post we highlight how a professor collaborated with the Seven Bridges Cancer Genomics Cloud (CGC) platform, developed by Velsera, to teach a class of undergraduate students to analyze cancer data in the cloud.
This collaboration eliminated the usually a lengthy skill acquisition period—learning to operate on a command line, how to execute bash scripts, or write python code—that presents a hurdle for interested beginning students. How can you design a very short intro course for absolute beginners without sacrificing most of your classroom time to equipment and software set up? Can you teach an intro to bioinformatics course in a quarter of a semester to first-year students and have them perform authentic scientific analyses with real data?
We caught up with Professor Jeremy Chien at UC Davis after he successfully did just that: taught 14 first-year biology students the basics of cancer genomics and transcriptomics, with hands-on analysis using real data, culminating in final projects presenting analyses of differential expression, fusion transcript prediction, SNP annotation, and ChIP-Seq. The depth and breadth of this short course was made possible by the Cancer Genomics Cloud.
In the interview, Dr. Chien talks about his decision to teach using the CGC, and why he’s glad he did so. “When I was thinking about and planning for students in this class, I looked into the institutional resources and it’s a lot more complicated.” The benefit of teaching the course with the CGC, he says, is that the students only had to make an account on the website, and then were able to immediately start using the software already publicly available on the CGC, such as Salmon and DESeq2, or STAR-Fusion. That removed barriers to entry that might otherwise have led to a lot of time spent on troubleshooting instead of instruction. In particular, the students reported that they appreciated the hands-on projects and demonstrations. “I was quite happy to see the feedback from students. One of the students actually said that…they had limited knowledge about what bioinformatics is” coming into the course. Now after the course, “They realized that they are just at the tip of the iceberg.”
Dr. Chien says that he plans to teach this course again and will also develop a higher-level course on Cancer Genomics that will use the CGC. When asked what he might do differently the second time around, Dr. Chien joked that the CGC made things a little too easy for the students. “For them it is just point and click…so they didn’t learn steps that are important.” He plans to address this next time by front loading the analyses, and then following them with a content-based lecture. “One of the feedbacks that I received from the students is that they actually like the Cancer Genomics Cloud platform so much that… we should cut down the lecture and do more of those bioinformatics hands-on analyses. What I’m thinking about doing is asking them to do more of those analyses, and then when we get the results and when I want them to analyze the results, at that point we can talk about important bioinformatics concepts.” This tactic is familiar to many instructors, who find that students are more engaged after they have had a personal experience working with and manipulating some object of study.
To those who are considering using the CGC as a teaching platform in their own classrooms, Dr. Chien’s advice is simple: “Just do it.” He says, “I like the fact that we are using the data that we are freshly generating, but also the beauty of the platform is that you also have the publicly accessible data. So if you don’t have your own data you can still teach the course with publicly available data. It is not as challenging or difficult as you think; there is a lot of help you can get from the CGC personnel. It was really good for the students and they got a lot out of it, so it would be really good if this kind of course was available everywhere.”
Dr. Chien contacted us prior to launching the course, and members of the CGC team including Dr. Zelia Worman and Dr. Cera Fisher presented introductory lectures and live demonstrations of running tasks in the first weeks of the course. If you are also interested in bringing the CGC to your classroom, contact us at firstname.lastname@example.org and let us know what you need. We are happy to consult, help find ways to offset costs, and even provide a few guest lectures!