Installation instructions

Table of contents

 

 

Introduction

Follow these instructions to install the RALSA package along with some additional software your system may require.

System requirements

Computer with minimum of 4GB of RAM (16GB or more recommended).

RALSA requires R version 4.0.0 or higher. RALSA will work on any operating system (Linux, MacOS, Windows, etc.) where R can be installed. The rest of the software requirements are platform dependent, see the installation instructions for the different operating systems below.

Installation

Linux

  1. Install R and RStudio using the package manager in your operating system.
  2. Start RStudio, run the following command and follow the instructions:
install.packages("RALSA", dependencies = TRUE)
  1. You are ready to use RALSA. Load the package by running the following command:
library(RALSA)

Enjoy!

 

MacOS

  1. Download R and RStudio, double click on the downloaded *.pkg files and follow the installation instructions.
  2. If your system does not already have XQuartz, you will need to download and install it as well.
  3. Start RStudio, run the following command and follow the instructions:
 install.packages("RALSA", dependencies = TRUE) 
  1. You are ready to use RALSA. Load the package by running the following command:
library(RALSA)

Enjoy!

 

Windows

Windows users will have to put some more effort because of some system dependencies that do not come with the operating system, as with Linux and MacOS.

  1. Download R and RStudio, double click on the downloaded *.exe files and follow the installation instructions.
  2. Download the Rtools package from CRAN website, read the installation instructions available on the download webpage, double click on the downloaded *.exe file and follow the installation instructions.
  3. Download Strawberry Perl, double click on the downloaded *.msi file and follow the installation instructions.
  4. Start RStudio, run the following command and follow the instructions:
install.packages("RALSA", dependencies = TRUE)
  1. You are ready to use RALSA. Load the package by running the following command:
library(RALSA)

Enjoy!