This workshop is designed to help guide a general scientific audience with little or no programming experience through the initial stages of learning the R programing language, with a focus on R fundamentals and best practices for working with code and data analysis projects. The program will feature both lecture and hands-on exercises, in near equal amounts, in order to give participants a practical learning experience.
- Main focus: coding fundamentals and best practices to support reproducible data analysis
- This workshop will not focus on specific statistical methods or their underlying theory.
- The workshop will have extensive hands-on components throughout, including coding exercises and question-and-answer sessions.
- To place the workshop in the context of the ASMS audience, the examples and exercises will be based on typical mass spectrometry data sets.
At the end of the workshop, participants should have a good understanding of:
- R programming fundamentals: basic syntax, how to work with RStudio, R data structures
- Basic data manipulation: how to read data files, tidy data, rearranging data
- Data plotting basics: how to use ggplot2, generate basic plots
- Reproducible data analysis: using scripts, functions, and RMarkdown to capture all steps of a project; good practices for coding style, documentation, project organization and versioning