Practical Genomics: Computational Tools for Cancer Research

2 Credits.

Provides an introduction to computational analysis of genomics datasets with applications in cancer research. Includes hands-on training in organizing, analyzing, and visualizing data using R, RStudio, and Bioconductor. Covers data manipulation, single-cell genomics, and differential gene expression analysis. Features live coding demonstrations, guided exercises, and capstone projects. Emphasizes real-world examples relevant to cancer biology and practical skills for integrating computational genomics into research workflows.