diff --git a/40-visualization.Rmd b/40-visualization.Rmd
index 56cc634..ec1159c 100644
--- a/40-visualization.Rmd
+++ b/40-visualization.Rmd
@@ -29,7 +29,7 @@ rna <- read.csv("data/rnaseq.csv")
```
The [Data Visualization Cheat
-Sheet](https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf)
+Sheet](https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-visualization.pdf)
will cover the basics and more advanced features of `ggplot2` and will
help, in addition to serve as a reminder, getting an overview of the
many data representations available in the package. The following
@@ -70,7 +70,7 @@ graph from the same 3 components: (1) a data set, (2) a coordinate system,
and (3) geoms — i.e. visual marks that represent data points [^three_comp_ggplot2].
[^three_comp_ggplot2]: Source: [Data Visualization Cheat
-Sheet](https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf).
+Sheet](https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-visualization.pdf).
To build a ggplot, we will use the following basic template that can
@@ -718,7 +718,7 @@ themes.
Let's come back to the faceted plot of mean expression by time and gene, colored by sex.
Take a look at the [**`ggplot2`** cheat
-sheet](https://github.com/rstudio/cheatsheets/blob/master/data-visualization-2.1.pdf)
+sheet](https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-visualization.pdf)
and think of ways you could improve the plot.
Now, we can change names of axes to something more informative than 'time'
@@ -808,7 +808,7 @@ ggplot(rna, aes(x = expression_log)) +
With all of this information in hand, please take another five minutes
to either improve one of the plots generated in this exercise or
create a beautiful graph of your own. Use the RStudio [`ggplot2` cheat
-sheet](https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf)
+sheet](https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-visualization.pdf)
for inspiration. Here are some ideas:
- See if you can change the thickness of the lines.
@@ -1026,16 +1026,6 @@ ggsave("fig_output/combo_plot_chromosome_sex.png", combo_plot,
Note: The parameters `width` and `height` also determine the font size
in the saved plot.
-
-```{r final-challenge, eval=FALSE, purl=TRUE, echo=FALSE}
-### Final plotting challenge:
-## With all of this information in hand, please take another five
-## minutes to either improve one of the plots generated in this
-## exercise or create a beautiful graph of your own. Use the RStudio
-## ggplot2 cheat sheet for inspiration:
-## https://www.rstudio.com/wp-content/uploads/2015/08/ggplot2-cheatsheet.pdf
-```
-
## Other packages for visualisation
`ggplot2` is a very powerful package that fits very nicely in our
diff --git a/60-rr.Rmd b/60-rr.Rmd
index bda8415..e779be8 100644
--- a/60-rr.Rmd
+++ b/60-rr.Rmd
@@ -207,9 +207,9 @@ rendered. Finish your report with a *Session information* section.
`r msmbstyle::question_end()`
The [R Markdown Cheat
-Sheet](https://github.com/rstudio/cheatsheets/raw/main/rmarkdown-2.0.pdf)
+Sheet](https://raw.githubusercontent.com/rstudio/cheatsheets/main/rmarkdown.pdf)
and [Reference
-Guide](https://www.rstudio.com/wp-content/uploads/2015/03/rmarkdown-reference.pdf)
+Guide](https://www.dataquest.io/blog/r-markdown-guide-cheatsheet/)
will help you with the markdown synatax, R code chunk options, and
RStudio utlisation.
diff --git a/docs/404.html b/docs/404.html
index d65ae29..111b2c0 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -13,7 +13,7 @@
-
+