This repo contains lecture slides and links to the Mind Expander exercises for the R workshop. These exercises are based upon the book, Computing Skills for Biologists
We would like to provide you with the opportunity to use R to automate the manipulation, analysis, and visualization of your own data set. You may work alone or in groups. Start by making a directory for your analysis, then copy your data to that directory and make a new R script to process the data. Try to complete all data processing, analysis, and visualization in R (and bash). Be sure to use commenting to describe what your code is doing and employ best practices in making your code readable by others.
If you were not able to bring your own data set, we will provide you with the option of analyzing any one of the data sets below that are provided with the book, Computing Skills for Biologists. The data can be found in the CSB repository that you cloned and have been working in. Notice that each data set is accompanied by a description file. We encourage you to look at the publication in which the data was reported. You can also refer to the book ("Computing Skills for Biologists") that is available in the class room for descriptions and ideas on what to do with the data on pages 295-298 & 335-336.
Self-Incompatibility in Plants - CSB/r/data/Goldberg2010*
Body Mass of Mammals - CSB/r/data/Smith2003*
Leaf Area Using Image Processing - CSB/r/data/leafarea/
Titles and Citations - CSB/r/data/Letchford2015*
Life History in Songbirds - CSB/data_wrangling/data/Martin2015*
Drosophilidae Wings - CSB/data_wrangling/data/Bolstad2015*
Extinction Risk Meta-Analysis - CSB/data_wrangling/data/Urban2015
We would like each group to create a GitHub repository with their project. The repository should include a readme.MD file that describes the files (and directories).
We will conclude the R portion of the workshop with a mini symposium after lunch on Tuesday. Each group will have 5 minutes or less to present so that we can finish by the mid afternoon break. We recommend limiting the number of slides (<5). You can spend Tuesday morning completing your analysis and making the presentation. Each presentation should include a prominent link the GitHub repository and at least one data visualization or statistical table made with R.