4 `WebR` Playground

4.1 Introduction

This page provides a WebR cell for use as a playground to experiment with example datasets, and describes how to include WebR on other Quarto pages.

WebR documentation

4.2 Playground

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```{webr-r}
# Use this WebR cell to experiment with using R. You can do almost anything
# by typing in this code cell that you can do in R, including plotting graphs.
#
# Why not try the command:
#
# plot(penguins)
#
# and click the "Run code" icon?

```

4.3 Examples to try

The penguins dataset contains data about three different species of penguins. You can use the R commands below to investigate the data:

glimpse(penguins)  # look at the format of the dataset
plot(penguins)     # plot a visual overview of the dataset

# Plot the count of penguins in each species as a bar chart
ggplot(penguins, aes(species, fill=species)) + geom_bar()

# Break down the distribution by species in a facet plot
ggplot(penguins, aes(species, fill=species)) + geom_bar() + facet_wrap(~sex)

# Make a box and whisker plot of penguin body mass by species:
ggplot(penguins, aes(x=species, y=body_mass_g, fill=species)) + geom_boxplot()

# Plot the body mass for each sex side-by-side
ggplot(penguins, aes(x=species, y=body_mass_g, fill=sex)) + geom_boxplot()

# Investigate correlation between body mass and flipper length:
ggplot(penguins, aes(x=body_mass_g, y=flipper_length_mm)) + geom_point()

# Colour datapoints by species:
ggplot(penguins, aes(x=body_mass_g, y=flipper_length_mm, colour=species)) +
         geom_point()

# Fit a linear regression to each species separately:
ggplot(penguins, aes(x=body_mass_g, y=flipper_length_mm, colour=species)) +
         geom_point() +
         geom_smooth(method="lm")

One of our BM214 workshops involves a WebR-supported interactive exercise involving simulated reporter curves.

Here, we have downloaded some data from the online repository and made it available as though it was a dataset on the filesystem, reporter_curves.csv.

# Load reporter experiment data
data <- read.csv("reporter_curves.csv")

glimpse(data)  # Summarise the data format

# Plot absorbance against concentration as a facet plot
ggplot(data, aes(x=conc, y=abs_ratio, color=sample)) + geom_point() +
  geom_line() + facet_wrap(~sample)

R comes with a number of example datasets you can practice with, including:

mtcars: fuel consumption and other statistic for 32 automobiles
Titanic: the fates of passengers from the maiden voyage of the ocean liner Titanic

You can see a full list by running the command

library(help = "datasets")

4.4 Setting up `WebR`

There are three important elements to including WebR on a Quarto page: the YAML header, the setup code block, and the WebR cell.

You can see an example of how to set up WebR on any Quarto page by inspecting the .qmd source for this page.

4.4.1 YAML header

To use WebR on a Quarto page, you need to include an appropriate YAML header at the top of the page:

---
webr:
  packages: ["tidyverse", "palmerpenguins"]
filters:
  - webr
---

Packages to be imported into WebR should be specified in the list, as tidyverse and palmerpenguins are, here. The webr filter must be loaded.

4.4.2 `WebR` setup block

There is a special R code block needed to prepare the WebR instance. For this page, the code block

```{webr-r}
#| context: setup

# Download reporter data
download.file('https://raw.githubusercontent.com/sipbs-compbiol/BM214-Workshop-3/main/assets/data/reporter_curves.csv', 'reporter_curves.csv')

library(palmerpenguins)
library(tidyverse)
```

declares that it has the setup context, so will be run when the WebR instance starts. The download.file() call pulls the reporter_curves.csv file from a GitHub repository and makes it available in WebR, as if it were a real file, with the name reporter_curves.csv. The last three lines import R packages into the WebR environment.

4.4.3 The `WebR` code cell

The minimal WebR code cell looks like this:

```{webr-r}
```

but it is more helpful, and more usual, to include some example code or comments, as in the example below:

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```{webr-r}
# You can use `R` as a calculator

1 * sin(1)
```