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 @@ - +