CELSeq Sample Sheet Generator

Welcome to the celseq-sample-sheet-generator repository.

SPECIAL ATTRIBUTION: We would like to thank WEHI Senior Research Officer Marek Cmero for developing the FACS merge logic used for this project. The code can be found under the scripts directory in operations.py.

This codebase contains all assets that will be deployed onto WEHI's Milton HPC via R Shiny. For details on the goals and implementation of this project visit the GMM wiki page.

This markdown file contains the following contents:

1. Directory Structure
2. Running This Application
3. Prerequisites
4. Sister Repository
5. Acknowledgements

Directory Structure

• server.R: The entry point to this application
• setup.R: Used for initialisating this application
• ui.R: Provides the frontend interface
• R: A sub-directory that contains R components
• scripts: Python files that handle merge logic (developed by WEHI Senior Research Officer, Marek Cmero)
• data.zip: Contains the sample data to demo the application
• markdown_assets: Stores images used for markdown files and the GMM wiki
• archive.zip: Contains the original contents of the Python/Flask application developed by Marek Cmero

Running This Application

The VIDEO below provides detailed instructions for setting up and running this application on MacOS/Linux. This Shiny R application is designed to assist in the processing and analysis of genomics metadata through an interactive interface.

Note: For Windows users, manual configuration of Python virtual environments and R dependencies is required due to package conflicts. Unfortunately, we do not have an automated solution for Windows at this time.

Prerequisites

Before proceeding, ensure you have the following prerequisites installed on your system:

• Git: For cloning the repository.
• R: The application is built in R, so ensure you have R installed.
• RStudio (Optional): For a more user-friendly experience running the app locally.

To run the application locally, you can use RStudio or the R console. Here are the steps for both methods:

Using RStudio

1. Open RStudio: Start RStudio on your local machine.
2. Open the app.R Script: Go to File > Open File and navigate to the location of your app.R script.
3. Run the App: Click the 'Run App' button in the RStudio interface to start the application.

Using R Console

1. Start the R Console: Open the R console on your machine.

2. Run the App: Execute the following command in the R console to start the application:

   shiny::runApp()

Using R Terminal

Alternatively, you can use the terminal to run the application:

1. Navigate to the App Directory: Use the cd command to navigate to the directory containing your app.R script.

2. Run the App: Execute the app.R script using RScript:

   RScript app.R

If you encounter issues, ensure you have the latest versions of R and RStudio. For permission errors, run RStudio as an administrator or use sudo on Linux/MacOS.

Windows users may need to manually configure environments and dependencies due to package conflicts.

Sister Repository

Please note that the R Shiny components of this codebase was migrated from the Genomics-Metadata-Multiplexing (GMM) repository.

Acknowledgements

We extend our gratitude to all contributors to the Genomics Metadata Multiplexing project. For a complete list of contributors, please visit the Contributors wiki page.