R Club

When: Wednesdays at 12:00 noon
Where: Vail 513
Purpose: Enhancing data analysis skills; facilitating collaborative bioinformatics and biostatistical research with an emphasis on R.

Everyone is welcome! Lunch is provided.

Contact: Katja Koeppen

Katja Koeppen and Tom Hampton, R Club facilitators

What is R?

  • R is a general-purpose statistical programming environment you can download for free. It works on a wide variety of computer platforms including Windows, Mac and linux. R Studio makes R substantially easier to use.
  • R can be augmented by downloading up to 15,000 task-specific CRAN packages to perform a wide array of analytical tasks. Bioconductor con
    tains addition packages (1,741) annotations (948) experimental data (371) and workflows (27) relevant to
    biology.

Needless to say, R is extremely powerful, and one of the things we do in R Club is help people become acquainted with what R can do. We emphasize hands-on presentations to provide R learners of all levels new experience and practice analyzing data and sharing their knowledge.

Topics covered in 2018-2019 included:

  • Choosing The Right Statistical Approach
  • Conceptual introduction to Linear Models for Biomedical Research
  • Subsetting R Data Frames Using grep() and Logic Statements
  • Machine Learning Approaches
  • Using base R, gplots, and ggplot2 to Visualize a Complex Experiment
  • Power Calculation in R
  • Hierarchical Clustering and PCA in R
  • Automating R Analyses Using Apply
  • Transcriptomics of Staphylococcus aureus in R
  • Single-cell Seq data exploration in R
  • Data Normalization, Philosophy and Practice in R
  • R in the lab – Assessing Correlation
  • Rentrez: Using R to Collect Data From NCBI
  • Analyzing Bacterial Growth Curve Data in R
  • Practice with Familiar Statistical Tests
  • Data Wrangling
  • Using CART Models to Link Data to Outcomes
  • Differential Gene Expression Analysis Experience
  • Experience using R to analyze microbiome data
  • BioMart shopping with the biomaRt package
  • Dose Response Curve Estimation in R

R scripts and slides are available on our Slack group.

Projects R Club participants have been working on include ScanGEO and PAPE.