This is a collection of document templates, available through R, from your friends at the University of Miami (UM). \(R+UM=rUM\)

The rUM package will help you create research manuscripts by removing the configuration hassles commonly encountered when learning to write papers using R. rUM will initialize a new RStudio project and a Quarto file that includes the outline for a research paper. The Quarto file comes preconfigured with a YAML header (don’t worry if you don’t know what that means yet) with code chunks to load the tidyverse and conflicted packages. Manuscript sections have been created for Introduction, Methods, Results, Conclusion, and References. The project also includes a .gitignore file which is designed to help protect against accidentally leaking data when using git with websites like

rUM’s documentation can be found here:

How do I get quarto and rUM? (Add a “quart o’ rUM”!)

  1. Modern version RStudio (v2022.07 or later) ships with Quarto but you can install the latest version of Quarto from here.

  2. Add rUM to your computer by:

    • using RStudio: click on the Packages tab in the bottom right windowpane, click the Install button, type rUM, and click Install.
    • downloading rUM from CRAN and installing it by running this code in R console:
    • downloading the latest version of rUM from GitHub by running commands into the R console:
    if (!requireNamespace("remotes")) install.packages("remotes")
  3. Use rUM by running this in the console of RStudio:

Ordering rUM from the Menu

To create a research project that uses rUM, follow these steps. This will initialize a new RStudio project that has an analysis.qmd Quarto file using the tidyverse and conflicted packages and some other useful files which are described below.

  1. Using the RStudio menus, choose: File > New Project > New Directory

  2. Scroll down and then select rUM Research Project Template

  3. Specify the location of where your research project will be saved

Add rUM into an existing folder/directory that does not have an RStudio project.

What if you have already created a folder containing the important files for your project? Create a new project in your existing folder! This will now be your project directory (complete with a .Rproj file).

  1. Navigate to File > New Project > Existing Directory

  2. Specify the location of where your research project will be saved

  3. Run the following script in your console:

# Change the text inside the quotes on the next line to indicate the path to your folder/directory.
PATH <- "~/Documents/blah"   

make_project(PATH, type = "Quarto (analysis.qmd)")

What is in the project? (What is served with your rUM?)

A new project directory is created and it will be populated with these files:

  • An aggressive .gitignore to help prevent the unintended sharing of sensitive study information or protected health information (PHI).
  • analysis.qmd is a Quarto template for writing your research project. It has a preconfigured YAML header; Introduction, Methods, Results, Conclusion, and Reference sections; and a code chunk to construct your bibliography using knitr::write_bib().
  • An empty folder named data. This folder is listed within the .gitignore. That means that git should not track these files. This should help prevent data leakage but be sure to talk to a data security expert before sharing any biomedical projects on websites like GitHub.
  • A .Rproj file with the same name as your project folder.
  • Two text files, packages.bib and references.bib, which are used to hold details for your paper’s bibliography. Refer to the Methods and References sections, respectively, within the analysis.qmd file for initial examples of how to add/use references.
  • the-new-england-journal-of-medicine.csl is the citation style language (CSL) based on the New England Journal of Medicine requirements.

Newly created files:



If you are new to R, ignore this.

#> R version 4.4.0 (2024-04-24)
#> Platform: x86_64-apple-darwin20
#> Running under: macOS Monterey 12.7.5
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib 
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> time zone: America/New_York
#> tzcode source: internal
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> loaded via a namespace (and not attached):
#>  [1] vctrs_0.6.5       cli_3.6.2         knitr_1.46        rlang_1.1.3      
#>  [5] xfun_0.43         purrr_1.0.2       textshaping_0.3.7 jsonlite_1.8.8   
#>  [9] htmltools_0.5.8.1 ragg_1.3.0        sass_0.4.9        rmarkdown_2.26   
#> [13] evaluate_0.23     jquerylib_0.1.4   fastmap_1.1.1     yaml_2.3.8       
#> [17] lifecycle_1.0.4   memoise_2.0.1     compiler_4.4.0    fs_1.6.4         
#> [21] htmlwidgets_1.6.4 rstudioapi_0.16.0 systemfonts_1.0.6 digest_0.6.35    
#> [25] R6_2.5.1          magrittr_2.0.3    bslib_0.7.0       tools_4.4.0      
#> [29] pkgdown_2.0.9     cachem_1.0.8      desc_1.4.3