Gene Expression and Data Analysis Pipeline Using Cancer BioPortal in the Classroom†

Abstract

At institutions with an emphasis on authentic research experiences as an integral part of the biology curriculum, COVID created a huge challenge for course instructors whose learning objectives were designed for such experiences. Moving such laboratory experiences online when remote learning became necessary has resulted in a new model for CUREs that utilizes free online databases to provide not only a novel research experience for students, but also the opportunity to engage in big data analysis. ABSTRACT At institutions with an emphasis on authentic research experiences as an integral part of the biology curriculum, COVID created a huge challenge for course instructors whose learning objectives were designed for such experiences. Moving such laboratory experiences online when remote learning became necessary has resulted in a new model for CUREs that utilizes free online databases to provide not only a novel research experience for students, but also the opportunity to engage in big data analysis. Cancer BioPortal (cBioPortal) is an open-access collective cancer research resource for storing and exploring clinical, genomic, proteomic, and transcriptomic data. cBioPortal eliminates the computational barrier of interpreting complex genomic data by providing easily understandable visualization that can be interpreted and translated into relevant biological insights. Because no prior computational knowledge is required, cBioPortal is an ideal educational tool for either in-person or distance learning environments. We developed a pedagogical approach, video tutorials, and data analysis workflows centered on using cBioPortal. Pedagogically, students develop an initial research outline that is continually updated and graded throughout the project. Progress during the project or course is assessed by a series of student presentations that are 5 to 15 min in length and are aimed at explaining the approach used in data acquisition, interpretation of the data, and relevance to the initial hypothesis. While cancer-specific, this analysis platform appeals to a wide range of classes and student interests. Further, the project has been successfully done both as an independent research experience and as part of a virtual class-based research project.