Why Quarto?

Max Czapanskiy

Why Quarto?

I barely wrapped my head around R Markdown. Now I have to learn something new?

It’s just friendlier

  • Backwards compatible (most everything you learned still works)

  • Consistent syntax (smooths over some weird R Markdown bumps)

  • Multi-language support (if that applies to you in the future)

Context: literate programming

  • Combine text, code, and outputs (figures etc). Great for scientific analysis!

  • Useful for all stages of the scientific analysis pipeline

    • Exploratory analysis (with collaborators!)

    • Technical writing (like cross-references and citations!)

    • Science communication (websites and more!)

Exploratory analysis (with collaborators!)

Project structure:

Exploratory analysis (with collaborators!)

Park downhill

  • You’re going to take breaks

  • Quarto keeps your notes, code, and figures in sync

  • Jump back in faster!

Productive 1-on-1 and team meetings

  • Send an email with links to updates

  • Keep progress in context

  • More in depth feedback, better planning

Communicating your science (technical writing)

  • Create a figure in code

  • Give it a name e.g., fig-regression

  • Cross-reference it with @fig-regression

  • Quarto turns it into Figure 1

#| label: fig-regression
#| fig-cap: y is correlated with x, isn't that swell?

dat <- tibble(
  x = runif(25),
  y = 3 * x + 1 + rnorm(25)
ggplot(dat, aes(x, y)) +
  geom_point() +
  geom_smooth(method = "lm", formula = y ~ x) +

Figure 1: y is correlated with x, isn’t that swell?

Communicating your science (references)

  • Look up the DOI

  • Use RStudio crossref lookup

  • Turn @10.3389/fphys.2022.917976

  • Into Czapanskiy and Beltran (2022)



Czapanskiy, Max F., and Roxanne S. Beltran. 2022. “How Reproducibility Will Accelerate Discovery Through Collaboration in Physio-Logging.” Frontiers in Physiology 13 (July). https://doi.org/10.3389/fphys.2022.917976.