tidyproteomics-interactive

This repository contains a Shiny application for interactively working with the R package {tidyproteomics}. Users may upload their protein- or peptide-level data for abundance subsetting, contaminant removal, abundance normalization, differential expression analysis, and ontology enrichment.

Using the application

Instructions for this application are available on its dedicated documentation page.

This application is hosted for public use by the Proteome Exploration Laboratory at the Beckman Institute at Caltech:

bioinformatics.pel.caltech.edu/tidyproteomics/

You may also run the application locally by following the instructions below.

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Local installation with Docker

The application is available as a Docker image on Docker Hub. To use the application locally, follow these instructions:

1. Clone this repository to a local directory using

   $ git clone https://github.com/ejmackrell/tidyproteomics-interactive <dir>

2. Download, install, and start Docker Desktop

3. Navigate to the directory and run the command

   $ docker compose up

   to pull the Docker image, build a Docker container, and run the application.

You may access the running application at http://localhost:3838. To change the port from the default 3838, edit the specification for ports in docker-compose.yml (e.g., to 5000:3838 for accessing the application at port 5000).

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Local installation with RStudio

You can also run and modify the application in RStudio by following the instructions below.

Cloning the repository in RStudio

1. Install {renv} (if it is not installed already) by executing

   install.packages("renv")
   

   in the R console.

2. Create a new version-controlled project in RStudio and provide the URL for this repository.

Restoring the project

1. Once the project is opened in your RStudio session, run the command

   renv::activate()

   to load the project environment, which should download the appropriate version of {BiocManager}.

2. Restore the project with the command

   renv::restore()

   to install all of the packages required for the project. If the repository for a Bioconductor package is not identified, you can manually install these packages individually by executing

   renv::install("bioc::{package name}")

   or instead as a group by specifying Bioconductor repositories with

   renv::restore(repos = BiocManager::repositories())

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Citation

If you use this application for your research, please cite our article.

Jones, J., MacKrell, E.J., Wang, TY. et al. Tidyproteomics: an open-source R package and data object for quantitative proteomics post analysis and visualization. BMC Bioinformatics 24, 239 (2023).