This course is compiled automatically on 2023-07-18
The course is tested and available on MacOS, Windows and
Ubuntu Linux for R version 4.3.0 (2023-04-21)
This course introduces how to code in R in a reproducible way. Two parallel methods are presented: Rmarkdown and Git. Together, Rmarkdown and Git allow you to generate analysis that is fully integrated with the results, session information is preserved and it is all version controlled so you can track changes as your analysis evolves.
Course material is available as HTML presentations or single page document. An exercise is available at the end.
Course material and exercises are available to view as rendered HTML at https://rockefelleruniversity.github.io/RU_reproducibleR/. All material is available to download under GPL v2 license.
Conda can be installed using the Herper package.
install.packages("Herper")
library(Herper)
install_CondaTools(tools = "python", env = "test")
Some people have errors running this command. Often this is the case for newer Macs with the ARM chip. The newest version of Herper on GitHub should help.
install.packages("devtools")
library(devtools)
devtools::install_github("https://github.com/RockefellerUniversity/Herper.git")
library(Herper)
install_CondaTools(tools = "python", env = "test")
Alternatively Miniconda can be installed manually by going to the Conda website.
Git is available from the projects website here. Follow the instructions here for your operating system.
Some user may already have Git installed. To test you can just run the code below.
git --version
R can be installed from the R-project website.
The R website can be found here http://www.r-project.org/.
The download links and associated installation instructions for multiple platforms can be found below provided by Revolution Analytics. https://cran.revolutionanalytics.com
We recommend installing R 4.3.0 as this is the version used to compile the course. Direct downloads for R 4.3.0 for the main platforms can be found below:
RStudio can be installed from the RStudio website.
RStudio can be downloaded for all platforms at the link below
https://rstudio.com/products/rstudio/download/
install.packages('BiocManager')
BiocManager::install('RockefellerUniversity/RU_reproducibleR',subdir='reproducibility')
install.packages('BiocManager')
BiocManager::install('methods')
BiocManager::install('ggplot2')
BiocManager::install('rmarkdown')
BiocManager::install('tidyverse')
BiocManager::install('knitr')
BiocManager::install('gh')
BiocManager::install('formatR')
BiocManager::install('reticulate')
BiocManager::install('Herper')
BiocManager::install('renv')
BiocManager::install('testthat')
BiocManager::install('yaml')
In Reproducible R and R packages, we will review how to install and manage R packages
Session sections:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
In Herper and Conda environments we will review how to manage conda environments using Herper.
Session sections:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
In Docker we will review the basics of Docker Containers.
Session sections:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
In Git and GitHub we will review the widely used version control and web hosting systems.
Session sections:
The html slide presentation can be found at this link Slide
The single page html presentation can be found at this link Single Page
The code use in the presentations can be found at R code
For advice, help and comments for the material covered in this course please contact us at the issues page associated to this course.
The link to the help pages can be found here
If you would like contact us about general bioinformatics advice, support or collaboration, please contact us the Bioinformatics Resource Center at brc@rockefeller.edu.