Section outline

  • Lecture: Introduction to Data Science & the R language

    • Data Science in biomedicine: goals and challenges
    • The R language and why it’s great for biomedical data
    • The R package ecosystem: CRAN, Bioconductor, GitHub
    • The RStudio Integrated Development Environment (IDE)
    • Rmarkdown, Jupyter notebooks, RStudio notebooks
    • Base R vs. “tidyverse” vs. data.table

    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):


  • Lecture: Data input/output, data types & structures, indexing, flow control

    • Reading data from CSV files, Excel spreadsheets
    • R data structures and data types; type conversions
      • Types: logical, integer, double, complex, character
      • Structures: vector, matrix, array, list, data.frame
      • Factors
      • class(), typeof(), str()
    • Indexing: filter cases, select variables
      • bracket notation
      • subset(), split()
      • Logical vs integer indexing; which
    • Long <-> wide data conversions
    • Saving data to .csv, .rds, .RData, .xlsx
    • Logical operations

    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: Flow control; Data summarization, aggregation; vectorization; functional programming

    • Flow control: for loops, if-then-else, while
    • Summarize statistics
    • Aggregate data
    • Vectorized operations
      • apply(), lapply(), sapply(), vapply(), tapply(), mapply()
      • by(), subset(), aggregate()
      • Reduce, Filter, Find, Position, Map, Negate
      • The pipe operator %>%
    • Functions in R
      • Functions as first class objects
      • do.call()

    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407


    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: Visualization

    • Visualization before and after data preprocessing.
    • The base and grid graphics systems; ggplot2.
    • Histograms, density plots, barplots, box plots, heatmaps, scatterplots.
    • Application: Genomics pipeline


    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407


    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: Reproducibility; Writing reports with Rmarkdown; Specialized data sources; Version control and code sharing

    • Reproducible reports with Rmarkdown.
    • Using git and GitHub for version control and code sharing


    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture:  Writing functions; Environments & scoping; Writing documentation; Performance profiling

    • Writing your own functions to streamline your data processing pipelines.
    • R environments and scoping.
    • Reading (others’) R code.
    • Writing documentation using roxygen2.
    • Profiling code


    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: Data preprocessing, imputation, dimensionality reduction; table joins

    • Handling missing values: imputation, last observation carried forward.
    • Categorical data: nominal vs ordinal
    • Standardization / feature scaling
    • Dimensionality reduction for high dimensional inputs.
    • Merging data sources: (SQL-type) join operations between tables: inner, full/left/right outer joins.


    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1406 (Please note room changed)

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: String operations; text manipulation and regular expressions; optimization


    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: Resampling; Mass-univariate testing; Intro to Machine Learning

    Faculty:  Stathis Gennatas


    Location: 
    Mission Hall 1407


    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

  • Lecture: Efficient data analysis with data.table

    Faculty:  Stathis Gennatas


    Location: 
     Zoom only

    Zoom Link: https://stanford.zoom.us/j/875634241 or +1 650 724 9799 (Meeting ID: 875 634 241)

    • Session Slides:

    • Session Audio/Video Recording (Access restricted to registered students):

    • Watch Media Resource
      Not available unless: You belong to a group in Registered Students Only
  • Lecture: Course Review, Q&A,  project presentations

    Presentations & handing in of completed projects

    Faculty:  Stathis Gennatas


    Location: 
     Zoom only

    Zoom Link: https://stanford.zoom.us/j/875634241 or +1 650 724 9799 (Meeting ID: 875 634 241)

    • Session Slides

    • Session Audio/Video Recording (Access restricted to registered students):

    • Watch Media Resource
      Not available unless: You belong to a group in Registered Students Only