Many facets of modern biological research involve the analysis of RNA to understand how cells control gene expression. These experiments involve powerful new sequencing methods that produce large data sets and require sophisticated bioinformatic analysis. In the Spring of 2016, faculty at the University of Colorado Anschutz Medical Campus were awarded $20 million to start the RNA Bioscience Initiative. To alleviate the bottleneck in analysis of these data sets, the RBI started the Informatic Fellows program and recruited postdoctoral fellows to develop and apply bioinformatic approaches and to educate other trainees on the use of these methods in their own research.
A unique feature of the program is that Fellows are card-carrying RNA biologists who have significant training at the lab bench. So while they no longer do “wet” experiments themselves, this background gives them a unique perspective on RNA-related research and has been instrumental in helping collaborators ask and answer fundamental questions in RNA biology.
It’s an exciting time to be an RNA biologist capable of analyzing large sequencing data sets. We discover something new every day in our collaborators’ data sets and are capitalizing on our unique capabilities to push the limits of RNA sequencing technologies.
The goal of the Informatic Fellows program is train the next generation of bioinformatic analysts who span the disciplines required for completing RNA sequencing experiments including design, execution, and analysis.
The Fellows divide their time between bioinformatic collaborations with other groups on campus, internal projects involving software and method development, and teaching.
Their training involves several important areas of bioinformatic collaboration:
Experimental design. RNA sequencing experiments are easily conceptualized but require appropriate design to ensure rigorous analysis. Design considerations include experimental variables (e.g., replicates and conditions), sample preparation (e.g., RNA type and source), and the sequencing platform (e.g., short or long reads).
Analytical software development. Once analyses are codified, we have worked to create and disseminate software for broad use in the community. Software development combines fundamental design principles with coding skills in Python, R, and C/C++ . Software developed in the program is available on our Github page.
Exploratory data analysis. RNA sequencing experiments often yield more questions than answers, and their biology backgrounds have been essential in enabling the Fellows to identify meaningful signals in complex data sets. These exploratory analyses combine data mining and statistics to enable thorough investigation. Deliverables are often fully reproducible dynamic documents that facilitate a collaborator’s own data exploration.
Education. Our educational mission is to broadly disseminate the analytical skills required to analyze RNA sequencing experiments, and the Fellows participate in several teaching activities. These efforts have been impactful across campus, with many graduate students, PRAs, postdocs, and principal investigators benefiting from the Fellows’ expertise.