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Installation

There are multiple ways to use scLRSomatoDev, from a simple online version to a local installation for more intensive use.

Table of Contents

Before starting

Minimum System Requirements

  • Processor: 8+ cores (Intel/AMD)
  • Memory: 32GB RAM (64GB recommended for Docker)
  • Storage: 50GB+ free space
  • Display: 1920 x 1080 resolution or Higher
  • Operating System: Windows 10/11 (64-bit), macOS 10.15+, or Ubuntu 20.04+

Installation Tutorial Video

Watch this video tutorial for a visual guide through the complete installation process before proceeding with the steps below. don't hesitate to watch it multiple times or press pause if you need to.

The video above demonstrates the installation process. If you prefer text instructions or encounter issues, continue reading below.

Get the project files

You can get the files using one of the following methods:

  • Option A: Download ZIP

    • Navigate to the "Code" tab on the GitHub repository page.
    • Select "Download ZIP".
    • Extract the contents of the ZIP file to your desired location.

  • Option B: Git Clone

    • Open your terminal and run the following command: bash git clone https://github.com/Cortical-interactome/scLRSomatoDev.git

Download the required data

  • Visit our Zenodo repository (TODO: Finish Zenodo Repo + add URL).
  • Download the data.zip file.
  • Extract the contents into your scLRSomatoDev folder.
  • Verify your folder structure matches the following folder structure :

Folder structure

Run scLRSomatoDev

[!NOTE] Choose your preferred installation method below. Docker is recommended for most users as it provides a consistent, isolated environment.

Why Docker? Docker ensures all dependencies are properly configured and isolated from your system, making installation more reliable.

Prerequisites

1. Build the Docker Image

Open your terminal, navigate to the project's root directory (the one containing the Dockerfile), and run:

On Linux, Windows and macOS (Intel/AMD):

docker build -t sclrshiny .

On macOS (Apple Silicon):

docker buildx build --platform linux/amd64 -t sclrshiny .

The initial build may take around 20 minutes to download and install the required R packages. Subsequent builds will be much faster.

2. Run the Docker Container

To create a local container from the image you just built, run the appropriate command for your system from the project's root directory:

On Linux or macOS:

docker run --rm -p 3838:3838 -v "$(pwd)/Data:/app/Data" sclrshiny

On Windows (Command Prompt):

docker run --rm -p 3838:3838 -v "%cd%\\Data:/app/Data" sclrshiny

On Windows (PowerShell):

docker run --rm -p 3838:3838 -v "${PWD}\\Data:/app/Data" sclrshiny

This command mounts your local Data directory to the /app/Data directory inside the container, which is where the app expects to find the data.

3. Launch the App

After running the command, your terminal will display:

Listening on http://0.0.0.0:3838

The app will be available at http://localhost:3838. It may take a few moments to load.

You only need to build the image once. For future use, you can simply run the container and open the link in your web browser.

Success with Docker? Great! Jump to Next Steps to start using the app.
Having issues? Try the RStudio installation method below or check our troubleshooting guide.

Using RStudio

Alternative Method: If Docker doesn't work for your system or you prefer direct R development, use this RStudio-based installation. ← Back to Docker instructions

Prerequisites

Setup Instructions

  • Create a conda environment using the provided environment file:
conda env create -f environment_scLRSomatoDev.yml
  • Activate the environment:
conda activate r_env

  • Open RStudio and set the working directory to the scLRSomatoDev folder.

  • To run the Shiny app, click the 'Run' or 'Play' button in either the ui.r or server.r file or run the following command in the console:

shiny::runApp("app.R")

Troubleshooting

[!CAUTION] Need Help? This section provides solutions for common installation issues. If you're new to R package management, start with the basics above.
← Back to main installation methods | Report an issue

Since R can be tricky when managing dependencies, we have included a list of packages in the environment_scLRSomatoDev.yml file.

  • If you encounter an error, you may need to install the missing R packages. You can do this by running the following commands in the console:

for a single specific package: 

install.packages("package_name")

for multiple packages:

install.packages(c("package_name1", "package_name2", "package_name3"))

some packages might not be available on CRAN, you can install them from Bioconductor or github using the following command:

for Bioconductor packages:

BiocManager::install("package_name")

for github packages:

remotes::install_github("username/repo")

We are aware that R packages management and dependencies can be difficult. If you cannot find the package you need, you can ask for help on the issues page.

[!WARNING] Need Help? If you encounter any issues during installation, check our troubleshooting section above or ask for help on the issues page.

Next Steps

Once you have successfully installed the app, you can start exploring scLRSomatoDev's features and functionalities. Here are some recommended next steps:

Quick Start

  • Launch the app using the instructions in the Run scLRSomatoDev section above
  • Explore the interface - The app opens with an "Overview" page that introduces the main features

Learn More