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ConCISE

Concensus Classification from In Silico Elucidations

DOI Binder License: MIT

ConCISE utlizes the ClassyFire structural annotations provided by in silico tools such as SIRIUS* and CANOPUS** combined with networking tools from GNPS such as feature based molecular networking***.

ConCISE is in active development and not yet academically published. If utilized before publishing date please cite this repo. You can run this tool locally using the graphical user interface and command line interface, or on a virtual machine using the above binder link.

ConCISE works by finding consensus annotations of putative annotations using the ClassyFire ontologies which are supplied by GNPS for library spectral matches and in silico putative annotations.

If you have any questions contact Zach Quinlan.

Download links:

Graphical user interface

Command line interface

To use the CLI you will need to download the source code. The CLI code will run the workflow runner in the main workflow python file.

Arguments:

  • GNPS task ID
  • Canopus_summary file
  • Networking info file
  • export directory for consensus file (optional; default = current working directory)
  • Superclass percent consensus (optional; default = 50)
  • Class percent consensus (optional; default = 70)
  • Subclass percent consensus (optional; default = 70)
  • Use NPClassifier in place of ClassyFire Ontologies (True or False; e.g., ‘True’ will utilize NPClassifier ontologies for both library matches and in silico matches)
python3 src/conciseCLI.py 16616afa8edd490ea7e50cc316a20222 exampleFiles/canopus_summary.tsv exampleFiles/Node_info.tsv 50 70 70 False

Virtual machine run through myBinder

myBinder offers a free virtual machine to run the jupyter notebook.

Binder

Version History

Issues:

Help us improve ConCISE

  • For bug reports or feature requests please open an “issue” on this github repository
  • If you would like to contribute to the development of ConCISE for other applications fork this repository and make a pull request with your changes. Or reach out directly to us to see if these changes are already being implemented in beta updates.

Contributing to the Documentation:

Feel free to help us maintain the documentation!

Editing documentation

All documentation lives in _pages/ and can be editted in .md form.

Makine new documents

Create a new .md file in _pages/. To the top of the page add:

---
layout: posts
    # classes: wide
sidebar:
    nav: "Documentation"
---

Then add this new documnent to the _data/navigation.yml with the title and url

- title: Gui Widgets
  url: /_pages/guiWidgets/index.html

Citations:

*Dührkop, K., Fleischauer, M., Ludwig, M. et al. SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information. Nat Methods 16, 299–302 (2019). https://doi.org/10.1038/s41592-019-0344-8

**Kai Dührkop, Louis-Félix Nothias, Markus Fleischauer, Raphael Reher, Marcus Ludwig, Martin A. Hoffmann, Daniel Petras, William H. Gerwick, Juho Rousu, Pieter C. Dorrestein and Sebastian Böcker. Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra. Nature Biotechnology, 2020

***Wang, M., Carver, J., Phelan, V. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol 34, 828–837 (2016). https://doi.org/10.1038/nbt.3597; Nothias, LF., Petras, D., Schmid, R. et al. Feature-based molecular networking in the GNPS analysis environment. Nat Methods 17, 905–908 (2020). https://doi.org/10.1038/s41592-020-0933-6