OmicsQ: A Toolkit for Quantitative Omics Analysis

OmicsQ is a Shiny-based web application designed for preprocessing and quantitative analysis of Omics data. It streamlines the preparation of data for subsequent analysis using specialized tools such as PolySTest for statistical testing and VSClust for clustering analysis.

Run OmicsQ via your browser on our server: OmicsQ

Visit ComputProteomics Group Page for more information on related research and tools.

Key features

Interactivity: Easily browse the data and selectively analyze and visualize according to your needs.

User-Friendly Experience: Avoid installation issues by using the app directly in your browser, with a simple interface for easy navigation.

Flexibility: Easily upload multiple file formats (text, Excel) and use the automated assignment of sample groups and batches.

Data Pre-processing: Batch correction, normalization, filtering, and missing value filtering with visual feedback.

Web Service Integration: Submit processed data directly to the following tools:
PolySTest for statistical testing with proper treatment of missing data
VSClust for variance-sensitive clustering analysis also of incomplete data sets
ComplexBrowser for exploration of quantitative behavior of protein complexes (mainly applicable to proteomics data).

Data Export: Download the processed data or analysis results for further offline analysis.

Installation

OmicsQ can be run locally on your machine or via Docker. Pick the option that suits you best.

Option 1: Run Locally (R)

1. Install R (4.2 or newer) and optionally RStudio.

2. Install required packages. In an R session:

# CRAN packages
install.packages(c(
  "shiny", "shinyBS", "shinyWidgets", "shinycssloaders", "shinythemes",
  "shinyjs", "DT", "data.table", "readxl", "openxlsx", "stringdist",
  "limma", "matrixStats", "jsonlite", "gridExtra", "ggplot2", "gplots",
  "viridis", "ggrepel", "ggiraph"
))

# Bioconductor packages
install.packages("BiocManager")
BiocManager::install(c("MsCoreUtils", "BEclear", "sva", "UniProt.ws"), ask = FALSE)

3. Clone this repository and run the app from the repo root:

git clone https://github.com/computproteomics/OmicsQ.git
cd OmicsQ

shiny::runApp(".")

Option 2: Run with Docker

This bundles all dependencies and runs a Shiny server.

Build the image locally:

git clone https://github.com/computproteomics/OmicsQ.git
cd OmicsQ
docker build -t omicsq .

Run the container and expose on port 3838:

docker run --rm -p 3838:3838 omicsq

Open http://localhost:3838 in your browser.

Documentation and tutorial

For detailed instructions on how to use OmicsQ, please refer to the User Manual. There, you can also find a tutorial on how to use the app for your data analysis.

Workflow

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License

OmicsQ is released under the MIT License. See the LICENSE file for details.

Citation

If you use OmicsQ in your research, please cite our work:

Xuan-Tung Trinh et al. OmicsQ: A Toolkit for Quantitative Analysis of Omics Data. preprint

Contributing

We welcome contributions! Please submit a pull request or open an issue to get involved.

Contact

For questions, comments, or suggestions, please contact the development team at [[email protected]].