Working with RStudio and Git

What is Git

• A version control system that saves a snapshot of your project every time you make changes
• Each change has to be documented with a description of the changes
• If multiple people are working on the same project (or if one person works on it in multiple places), changes can be synced
• Syncing requires storing the project on a Git server (eg, GitHub)
• Since code is stored online, it’s easy to share with others
• GitHub is a free service, but requires that all code to be publicly available
  • this isn’t normally a problem for biologists, though you may want to ensure that your data are not included in the repository

The preferred workflow for Git

A realistic workflow for Git

Setup

• Installing RStudio
  • Available from https://www.rstudio.com
  • Appears to require EUR to install
• Installing GitHub Desktop
  • Available from https://desktop.github.com
  • For some reason, this seems to install with no difficulty
  • Create GitHub account and log into GitHub Desktop using these credentials
  • In theory, it is possible to run Git directly through RStudio, but:
    1. You would have to learn a new interface to use Git for any other project
    2. I can’t get it to work with the networked drive
• Cloning LearningMLwiN
  • Click on + in upper left corner of GitHub Desktop, then “Clone”
  • Select MixedModels/LearningMLwinN from the menu (if it doesn’t show up, ask me to add you to MixedModels)
  • Select destination folder
  • Open RStudio, click on project selector in upper right corner, and select “New Project”
  • Click on “Existing Directory” and navigate to cloned repository, then click “select folder” and “Create Project”
• Adding an Existing Project
  • Click on project selector in upper right corner of RStudio and select “New Project”
  • Click on “Existing Directory” and navigate to folder, then click “Select Folder” and “Create Project”
  • Click on + in upper left corner of GitHub Desktop, then “Create”
  • Navigate to folder and click OK
  • Give repository a name and create (note that redundant names in different locations on your file system will clash on the server)
• Starting from Scratch
  • Click on project selector in upper right corner of RStudio and select “New Project”
  • Click on “New Directory”, then “Empty Project”, then pick a project name and location
  • Click on + in upper left corner of GitHub Desktop, then “Create”
  • Navigate to folder and click OK
  • Give repository a name and create

Working with RStudio

• Collects all of the files associated with a project together
• Snippets of code from a script can be run on their own, or code can be entered directly into the console
• Nice GUIs for viewing and saving plots, importing data-sets, and viewing data-frames
• Work-spaces are automatically saved for each project
• I have not figured out an easy way to work on scripts that accept command line arguments

R Markdown

• Used to prepare this document
• Simple plain text syntax used to format document (this syntax is also used many other places, including GitHub)
• Code and output can be embedded:

library(lme4) #glmer
library(readr)
SchoolData<-read_tsv("https://raw.githubusercontent.com/MixedModels/LearningMLwinN/master/tutorial.txt")
SchoolData$school<-factor(SchoolData$school)
SchoolData$girl<-factor(SchoolData$girl)
MOD.1 <- lmer(normexam ~ standlrt + (1|school), data = SchoolData, REML=F)
summary(MOD.1)

## Linear mixed model fit by maximum likelihood  ['lmerMod']
## Formula: normexam ~ standlrt + (1 | school)
##    Data: SchoolData
## 
##      AIC      BIC   logLik deviance df.resid 
##   9366.7   9391.9  -4679.4   9358.7     4055 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.7192 -0.6290  0.0266  0.6850  3.2723 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  school   (Intercept) 0.09217  0.3036  
##  Residual             0.56594  0.7523  
## Number of obs: 4059, groups:  school, 65
## 
## Fixed effects:
##             Estimate Std. Error t value
## (Intercept) 0.001539   0.040031    0.04
## standlrt    0.563440   0.012469   45.19
## 
## Correlation of Fixed Effects:
##          (Intr)
## standlrt 0.008

• Plots can also be embedded without displaying the code: