As access to high throughput technology increases, the bottle-neck in biomedical research has shifted from generating data, to analyzing and integrating diverse data types. Addressing these needs requires that students and postdocs equip themselves with powerful tools for data mining and interrogation. This course focuses specifically on studying global gene expression (transcriptomics) through the use of the R programming environment and the bioconductor suite of bioinformatics packages – a versatile and robust collection tools for statistics and graphics. During this semester-long course, students work with real datasets and carry out all aspects of data analysis on their laptop.


The course is taught by Dan Beiting, Assistant Professor of Pathobiology at PennVet. Camila Amorim and Alex Berry, both post-docs, serve as teaching assistants.


Class meets every Wednesday from 3-5pm in the large lecture halls on the first floor of the Hill Pavilion (pictured in banner image above).

Course goals

  • Learn to analyze your own RNAseq data
  • Develop a lightweight and reusable RNAseq pipeline.
  • Learn best practices for working in R/bioconductor (extensible to other datatypes)
  • Learn the basics of ‘data science’
  • Learn how to report your analysis and results in a transparent and reproducible way

Target audience

This course is ideal for biomedical graduate students and postdocs who have little or no experience in bioinformatics.