guide_for_working_locally.qmd

# Guide for Working Locally {.unnumbered}

## Download Course Materials

1. Go to the [R for Bio Data Science RStudio Cloud Server](https://teaching.healthtech.dtu.dk/22100/rstudio.php)
1. Login using your credentials
1. In the file pane, navigate to your `projects`-directory, where (if you followed course instructions) you will find your `r_for_bio_data_science`-directory
1. Tick the box to the left of your `r_for_bio_data_science`-directory
1. Click the gear cog, which says `More`
1. Click `Export...`
1. You should now be prompted to download `r_for_bio_data_science.zip`
1. Click `Download`

## Download Course Slides

The course slides are available via the course site. They are self-contained `.html`-files and can be opened offline in a browser like e.g. google chrome. The slides can be downloaded as follows:

1. Go to the [Course Site](http://r4bds.github.io/)
1. In the menu on the left, choose a course lab and click it
1. Under `Schedule`, find and click the link to the lecture
1. Hit command+s (mac) or ctrl+s (windows) or choose file and then save depending on your OS
1. Put the downloaded `.html`-files where you want to save them.
1. Right click and choose open with or similar and then choose your favourite browser

## Installing R on your computer

1. Go to [The R Project for Statistical Computing](https://www.r-project.org)
1. Under `Getting Started` it says `To download R, please...`, click the `download R`-part
1. Scroll down and find `Denmark` and click
1. Click the `Aalborg University`-mirror link [https://mirrors.dotsrc.org/cran/](Aalborg University)
1. Under `Download and Install R`, click your appropriate OS Linux, macOS or Windows
    1. If you have Linux, you'll know what to do
    1. For mac, be aware that you have to choose either `R-4.3.2-arm64.pkg` or `R-4.3.2-x86_64.pkg` (versions as of 30-11-23) depending on whether you have a `M`- or an `Intel`-mac. This you can find out by clicking the apple in the upper left corner of your screen and select `About This Mac` and look at what is says next to `Chip`
    1. For Windows, there is a `install R for the first time`-guide you will have to follow.
  
If any of this is unclear, I'm absolutely sure, there will be tons of how-to-install-R tutorials on youtube

## Installing RStudio

1. Go to the [Posit](https://posit.co) site
1. Click `DOWNLOAD RSTUDIO` in the upper right corner
1. Under `RStudio Desktop`, click `DOWNLOAD RSTUDIO`
1. The first point `1: Install R` is covered above
1. Under `2: Install RStudio`, click the blue box below, it will vary depending on your OS, mine says `DOWNLOAD RSTUDIO DESKTOP FOR MACOS 11+`
1. Open the downloaded installer and follow the instructions

## Installing packages

Once you have downloaded and installed `R` and `RStudio`, you can start installing packages. E.g. we can install `Tidyverse` using the command:

```{r}
#| echo: true
#| eval: false

install.packages("tidyverse")
```

Look through the different exercise labs at the top, the packages you have been working with are stated.

## Open course materials

The downloaded course materials can simply be opened directly in `RStudio`, so be sure to organise them, so you can easily access them on your own computer.