The general structure of the course planned as:

Day 1 (Day 2? )

  • Basic R introduction
    • Data types
    • Control structures
    • Functions
    • Debugging

Day 2

  • Data Import
  • Data Wrangling
    • Tidying
    • Cleaning
    • Summarizing
  • Exploration
    • Visualization
    • Descriptive Statistics

Day 3

  • Inference
    • Statistical modeling
    • Interpretation

Day 4

  • Work with S4 objects
    • GRanges
    • SummarizedExperiment
    • example data analysis (Gene expression)

Day 5

  • Reproducible research

    • version control, git
    • RMarkdown
    • workflowr
  • Good programming practice