SIRIUS Merger Tool

Overview

The SIRIUS Merger Tool (SIRIUS Output Analyzer) is an interactive R Shiny application developed to organize, merge, and visualize the primary output files from the SIRIUS software suite.

This tool is specifically designed for chemoinformatics and metabolomics workflows, allowing users to effortlessly combine canopus_structure_summary.tsv and structure_identifications.tsv datasets. It provides rich, interactive visualizations of chemical classifications (ClassyFire and Natural Product Classifier) and generates combined data tables ready for downstream analysis.

🌐 Live Demo: Try the SIRIUS Merger Tool online!

Key Features

• Data Merging: Seamlessly merges CANOPUS structure summaries with structure identifications based on their feature IDs.
• Interactive Visualizations: Generates high-quality Pie Charts and Sunburst plots for both ClassyFire (Superclass, Class, Subclass) and NPC (Pathway, Superclass, Class) ontologies using plotly.
• Customizable Parameters:
  • Filter merged datasets by Mass Accuracy Threshold (ppm).
  • Group minor features into an "Others" category to clean up visualizations.
  • Manually customize colors for Sunburst plot root elements.
• Data Export: Download fully merged datasets, ppm-filtered datasets, and individual chemical class summary tables as .csv files.
• Custom Adduct Support: Automatically integrates custom adduct calculations via MetaboCoreUtils if provided.

Inputs Required

The app accepts standard .tsv output files directly from SIRIUS:

1. canopus_structure_summary.tsv (Required for plots and base summaries).
2. structure_identifications.tsv (Optional, required to unlock data merging and ppm filtering).

Local Installation

If you prefer to run the app locally rather than using the web version, you will need R and RStudio installed on your machine.

1. Clone the repository:

   git clone [https://github.com/froz9/SIRIUS_merger_tool.git](https://github.com/froz9/SIRIUS_merger_tool.git)
   cd SIRIUS_merger_tool
   

2. Install required R packages: Open R or RStudio and run the following command to install the necessary dependencies:

install.packages(c("shiny", "data.table", "dplyr", "plotly", "DT", "colourpicker", "BiocManager"))
BiocManager::install("MetaboCoreUtils")

3. Run the App: Open the app.R file in RStudio and click Run App, or execute the following in your R console:

shiny::runApp()

Usage Instructions

• Upload Data: Navigate to the sidebar and upload your canopus_structure_summary.tsv file.
• Merge (Optional): Upload your structure_identifications.tsv file to calculate mass accuracy and merge the tables.
• Adjust Parameters: Use the sliders to set your desired ppm mass accuracy threshold and the minimum count for grouping minor features into "Others" on the pie charts.
• Explore: Navigate through the tabs to view interactive ClassyFire and NPC plots. You can adjust the image download resolution scales directly above the plots.
• Download: Go to the "Downloads" tab to retrieve your merged data, filtered data, or individual classification summary tables.

Acknowledgments

This application was developed by Alan Hernandez. This work was supported by the Universidad Nacional Autónoma de México (UNAM) Postdoctoral Program (Lab. 125, School of Chemistry).

License

This project is licensed under the MIT License - see the LICENSE file for details.

For bug reports or feature requests, please open an issue on GitHub or contact the author at f9.alan@gmail.com.