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Network Annotation Propagation

Table of contents

Description

Network Annotation Propagation uses molecular networking to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations.

The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp

Graphical abstract

Figure 1. Representative scenarios of molecular networks obtained in an untargeted MS/MS experiment and possibilities for propagation. a) Introduction of molecular networking and library matching. b, c and d represent varying degree of spectral annotation in the network. e, f and g illustrate how the propagation of annotations can be used for each respective scenario (represented in the top panel). e) The Fusion scoring—The spectral library hit nodes (red) are employed to recalculate the score of candidate structures (grey shapes associated to nodes) for nodes having structure candidates from in silico fragmentation search (blue), based on their structural similarity (Represented by the green heatmaps, where darker green indicates a higher degree of similarity). f) and g) The Consensus scoring—a Consensus scoring can be used, based on the joint similarity of neighbors (pink nodes) for spectral library hits and in silico annotations (f), or in silico annotation only, when no library match is present (g).

Main citation

da Silva, R. R.; Wang, M.; Nothias, L.-F.; van der Hooft, J. J. J.; Caraballo-Rodríguez, A. M.; Fox, E.; Balunas, M. J.; Klassen, J. L.; Lopes, N. P.; Dorrestein, P. C. Propagating Annotations of Molecular Networks Using in Silico Fragmentation. PLoS Comput. Biol. 2018, 14 (4), e1006089. http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006089

Other citations

NAP uses molecular networking on GNPS Wang, M.; Carver, J. J.; Phelan, V. V.; Sanchez, L. M.; Garg, N.; Peng, Y.; Nguyen, D. D.; Watrous, J.; Kapono, C. A.; Luzzatto-Knaan, T.; et al. Sharing and Community Curation of Mass Spectrometry Data with Global Natural Products Social Molecular Networking. Nat. Biotechnol. 2016, 34 (8), 828–837. https://www.nature.com/articles/nbt.3597

NAP uses MetFrag for in silico annotation Wolf, S.; Schmidt, S.; Müller-Hannemann, M.; Neumann, S. In Silico Fragmentation for Computer Assisted Identification of Metabolite Mass Spectra. BMC Bioinformatics 2010, 11 (1), 148. https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-148

NAP uses the Fusion concept, proposed on for MetFusion, for ranking improvement from spectral library. Gerlich, M.; Neumann, S. MetFusion: Integration of Compound Identification Strategies. J. Mass Spectrom. 2013, 48 (3), 291–298. https://onlinelibrary.wiley.com/doi/abs/10.1002/jms.3123

Running NAP on GNPS

The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp

Documentation

The documentation is available here: https://github.com/DorresteinLaboratory/NAP_ProteoSAFe/raw/master/supplementar_tool_manual_documentation.pdf

Creating a custom database

Description

Using the wep-app [Recommended]

A custom database can be used in NAP. First, the list of structures has to be processed with a web-app, before being used in NAP.

The web-app can be accessed at the following address: http://dorresteinappshub.ucsd.edu:5002/upload The input file consists of .txt file (tab separated) with two columns, the first one with the SMILES string, and the second one with the compound name (unique string). An example input file can be accessed here: https://raw.githubusercontent.com/DorresteinLaboratory/NAP_ProteoSAFe/master/formatdb/Euphorbia_Example_inhouse_database.txt

When completed, the results of the job will be sent to the email address provided. The .TSV file obtained can then be added to the NAP job interface [https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp]. NB: Note that the custom database will be added to the other databases selected.

Jupyter notebook [For developers]

The jupyter notebook [http://jupyter.org/install], and input template files are available in the following folder: https://github.com/DorresteinLaboratory/NAP_ProteoSAFe/tree/master/formatdb

Installation instructions

First, install Miniconda https://conda.io/miniconda.html

In Miniconda, install Jupyter notebook: https://jupyter.readthedocs.io/en/latest/install.html

pip3 install --upgrade pip
pip3 install jupyter

After that, create an environment with the following command:

conda create -n formatdb python=3
source activate formatdb
conda install -c rdkit rdkit
pip install pandas
pip install ipykernel
pip install requests
python -m ipykernel install --user --name formatdb --display-name formatdb
source deactivate

Note that Anaconda Navigator can used instead: https://docs.anaconda.com/anaconda/navigator/

Import the content of the following folder on your computer: https://github.com/DorresteinLaboratory/NAP_ProteoSAFe/tree/master/formatdb Activate the formatdb environment in conda, and open the formatdb.ipynb with Jupyter notebook. In the Jupyter notebook, set the new kernel -> On the top menu Kernel >> Change Kernel >> formatdb.

The resulting output can be uploaded on GNPS, and specified as input in the NAP workflow interface.

Installation for developers

Before installing NAP, install ProteoSAFe.

Make sure ProteoSAFe is running properly, you can learn more with the workflow developer resources.

Futher documentation can be found at Workflow XML file documentation.

After ProteoSAFe installation download MetFrag CL and place the jar file on the nap_ccms2/Snap directory. Please refer to MetFusion and MetFrag publications to learn more about the tools.

Edit the file install_all.txt to change the YOURPATHCONDAENV and YOURPATHTOOLSFOLDER variables. Alternatively, refer to ProteoSAFe documentation to encode the path at the tools xml file and avoid hardcoding.

After that, run the installation script to install the conda environment and all dependencies.

./install_all.txt

After installation move the nap_ccms2 folder to proteosafe/tools folder and nap_ccms2_workflow to proteosafe/workflows. On proteosafe/workflows rename nap_ccms2_workflow to nap_ccms2.

NAP was installed and tested under 

Linux 4.9.0-2-amd64 #1 SMP Debian 4.9.18-1 (2017-03-30) x86_64 GNU/Linux

Help and Troubleshooting

Refer to the documentation or open an issue on this GitHub repository, or post a message on the GNPS forum https://groups.google.com/forum/#!forum/molecular_networking_bug_reports

Licence

This repository is available under the following licence https://github.com/DorresteinLaboratory/NAP_ProteoSAFe/blob/master/LICENSE.txt