Appendix C — Extra exercises

C.1 Creating automatic analysis pipelines

C.1.1 Exercise: Update function to also calculate median and IQR

Time: ~8 minutes.

Let’s make a change to our function and test out how the tar_outdated() and tar_visnetwork() work.

  1. Open up the R/functions.R file.
  2. Add median and interquartile range (IQR) to the summarise() function, by adding it to the end of list(mean = mean, sd = sd), after the second sd. Note, IQR should look like iqr = IQR since we want the output columns to have a lowercase for the column names.
  3. Run tar_outdated() and tar_visnetwork() in the Console (or by using the Command Palette , then “targets outdated” or “targets visual”). What does it show?
  4. Style using the Palette (, then type “style file”). You might need to force a reformat if the code is too long by highlighting the line and using , then “reformat”.
  5. Run tar_make() in the Console or with the Palette (, then type “targets run”). Re-check for outdated targets and visualize the network again.
  6. Open up the Git interface and commit the changes to the Git history with or with the Palette (, then type “commit”).
Click for a potential solution. Only click if you are struggling or are out of time.
#' Calculate descriptive statistics of each metabolite.
#'
#' @param data Lipidomics dataset.
#'
#' @return A data.frame/tibble.
#'
descriptive_stats <- function(data) {
  data |>
    dplyr::group_by(metabolite) |>
    dplyr::summarise(dplyr::across(value, list(
      mean = mean,
      sd = sd,
      median = median,
      iqr = IQR
    ))) |>
    dplyr::mutate(dplyr::across(tidyselect::where(is.numeric), ~round(.x, digits = 1)))
}

C.2 A general approach to doing statistical analyses

C.2.1 Exercise: How would you define a linear regression with parsnip?

Time: ~10 minutes.

Using parsnip’s “Examples” vignette as well as the code we wrote for the logistic regression above as a template, write parsnip code that would define a simple (an engine of"lm") linear regression model. Begin by making a new Markdown header and code chunk at the bottom of the doc/learning.qmd file, like listed below:

## Exercises
### Linear regression model definition

```{r}

```

After writing the code, style the file using the Palette (, then type “style file”). We will eventually delete these exercise text in the Quarto file, but for now, commit the changes to the Git history with or with the Palette (, then type “commit”).

Click for the solution. Only click if you are struggling or are out of time.
linear_reg_specs <- linear_reg() |>
  set_engine("lm")