PCA with R

Welcome to the read-me file for the PCA workshop. In this repo, you are going to find the code and files we are going to use for the practical part of the workshop, together with the ppt associated with this training. In order to follow along you will have to pull this repository into Noteable.

Below are the steps to do so and get set.

On Noteable

Go to https://noteable.edina.ac.uk/login
Login with your EASE credentials
Select RStudio as a personal notebook server and press start
Go to File >New Project>Version Control>Git
Copy and Paste this repository URL https://github.com/DCS-training/PCA-2023 as the Repository URL
The Project directory name will filled in automatically but you can change it if you want your folder in Notable to have a different name
Decide where to locate the folder. By default, it will locate it in your home directory
Press Create Project

Congratulations you have now pulled the content of the repository on your Notable server space the last thing you need to do is to install the packages not already installed in Noteable.

Open the 'Install.R' file and run the code within it
Now you can open the 'PCA.R' file and you can follow along

On your own machine

R and RStudio

R and RStudio are separate downloads and installations. R is the underlying statistical computing environment, but using R alone is no fun. RStudio is a graphical integrated development environment (IDE) that makes using R much easier and more interactive. You need to install R before you install RStudio. After installing both programs, you will need to install some specific R packages within RStudio. Follow the instructions below for your operating system, and then follow the instructions to install tidyverse and RSQLite.

Windows

If you already have R and RStudio installed

Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.

To check which version of R you are using, start RStudio and the first thing that appears in the console indicates the version of R you are running. Alternatively, you can type sessionInfo(), which will also display which version of R you are running. Go on the CRAN website and check whether a more recent version is available. If so, please download and install it. You can check here for more information on how to remove old versions from your system if you wish to do so. {: .solution}

If you don't have R and RStudio installed

Download R from the CRAN website.

Run the .exe file that was just downloaded

Go to the RStudio download page

Under Installers select RStudio x.yy.zzz - Windows Vista/7/8/10 (where x, y, and z represent version numbers)

Double click the file to install it

Once it's installed, open RStudio to make sure it works and you don't get any error messages. {: .solution}

macOS

If you already have R and RStudio installed

Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.

To check the version of R you are using, start RStudio and the first thing that appears on the terminal indicates the version of R you are running. Alternatively, you can type sessionInfo(), which will also display which version of R you are running. Go on the CRAN website and check whether a more recent version is available. If so, please download and install it. {: .solution}

If you don't have R and RStudio installed

Download R from the CRAN website.

Select the .pkg file for the latest R version

Double click on the downloaded file to install R

It is also a good idea to install XQuartz (needed by some packages)

Go to the RStudio download page

Under Installers select RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit) (where x, y, and z represent version numbers)

Double click the file to install RStudio

Once it's installed, open RStudio to make sure it works and you don't get any error messages. {: .solution}

Linux

Follow the instructions for your distribution from CRAN, they provide information to get the most recent version of R for common distributions. For most distributions, you could use your package manager (e.g., for Debian/Ubuntu run sudo apt-get install r-base, and for Fedora sudo yum install R), but we don't recommend this approach as the versions provided by this are usually out of date. In any case, make sure you have at least R 3.5.1.
Go to the RStudio download page
Under Installers select the version that matches your distribution, and install it with your preferred method (e.g., with Debian/Ubuntu sudo dpkg -i rstudio-x.yy.zzz-amd64.deb at the terminal).
Once it's installed, open RStudio to make sure it works and you don't get any error messages.

Organizing your working directory

Using a consistent folder structure across your projects will help keep things organized, and will help you to find/file things in the future. This can be especially helpful when you have multiple projects. In general, you may create directories (folders) for scripts, data, and documents. If you want to learn more about how to get set have a look (https://datacarpentry.org/R-ecology-lesson/00-before-we-start.html)[https://datacarpentry.org/R-ecology-lesson/00-before-we-start.html]

License

This repository has a license

DCS-training / PCA-2023