These are resources to help students interested in developing foundational skills useful for computational biology. The basic section contains short introductions, and advanced resources are more complete references.

Basic resources and introductions

  1. Git and GitHub. Git can feel overwhelming, but just dive in and it will be worth your time.
  2. Markdown. Markdown is an easy-to-read, easy-to-write plain text format.
  3. R and Bioconductor. R is unparalleled for statistical packages and powerful data visualization.
  4. Python. Python is a nice general-purpose programming language
  5. Unix command line.
  6. YAML

Advanced resources and complete references

  1. Git and GitHub
  2. Markdown
  3. R
  4. Bioconductor
  5. Unix command line
  6. Python
  7. Programming concepts
  8. High-performance computing and SLURM. SLURM (the Simple Linux Utility for Resource Management) is the cluster workload manager used by Rivanna at UVA and at many high-performance clusters elsewhere. If you need to submit jobs to a cluster, learn SLURM.
  9. Visualization
  10. Writing
  11. Writing R/Bioconductor packages
  12. Workshops
    • For Bioinformatics workshops at UVA check out Bioconnector.