What have you enjoyed most about working on the CAVATICA platform?

I am thrilled that CAVATICA is very versatile about enabling users to port over data from various data repositories using retrieval options for both controlled and open data, and also offers capability to transfer/link data stored on various cloud platforms.

Could you describe your current research focus and its potential impact?

My recent research for the Open Pediatric Cancer project involved performing differential expression analysis for a large set of genes from various normal tissues and cancer tumors. This required a lot of computing resources and with CAVATICA, I was able to wrap the entire analysis into an app and parallelize it to process the data much faster. These results can be used for informing clinical research for more personalized pediatric cancer treatment increasing the chances for improved outcome.

What challenges have you encountered, and how have you overcome them using CAVATICA?

Processing data for differential expression analysis called for use of HPC, and given that my work was made open source, the potential consumers who may or may not have access to HPCs, I am glad I was able to wrap my scripts into CWLs and make the original scripts as well as CWLs public via a GitHub repository. Now researchers can create their own app on CAVATICA with my CWLs files, and have the flexibility to use the same datasets or bring their own to further their research goals.

How do you see your research evolving in the next few years?

Since my last project where I got to work hands-on with CAVATICA, I took on the challenge to work with our collaborators to help them use their proprietary data and/or other public data and trained them to use some of the pre-built public tools and workflows on CAVATICA, and also demonstrated to them how they can build custom apps. It gives me immense sense of satisfaction to have enabled other researchers to skip the software development and DevOps part and focus on analytical research.

Do you have any advice for others in the field who are new to CAVATICA?

I have been trained in SDLC and a bit of DevOps while working full time as a bioinformatics scientist, and I found that for students in academia or new grads who are starting out in the field of bioinformatics research, this platform can enable users to minimize the steep learning curve so they can focus on the scientific problem and spend less resources before they can reach their research goals. So my advice is, just get started with CAVATICA, and use their office hours as you need for additional help.