Knowledge and Data-driven Two-layer Networking for Accurate Metabolite Annotation in Untargeted Metabolomics
MrnAnnoAlgo3 is the core algorithm module of MetDNA3, designed to annotate metabolites through a two-layer interactive networking topology (knowledge-driven and data-driven) and recursive annotation propagation algorithms.
It provides a robust computational foundation for large-scale metabolomic studies.
The completed functions are provided in the MetDNA3 webserver (http://metdna.zhulab.cn) via a free registration.
The detailed tutorial was also provided in the webserver.
✨ Two-Layer Networking Topology
Integrates knowledge-driven (biochemical pathways, metabolic reaction networks) and data-driven (experimental MS2 similarity networks) layers for comprehensive and accurate metabolite annotation.
⚡ Recursive Annotation Propagation Algorithm
An efficient topology-based annotation propagation algorithm leveraging both network layers to enhance annotation coverage and accuracy.
📊 High Performance
Processes a typical untargeted metabolomics dataset in just one hour—over 10-fold faster than previous versions.
🔗 Seamless Integration
Designed as a core component of the MetDNA3 ecosystem. Note: Full MetDNA3 functionality requires additional modules.
# Install via devtools (ensure devtools is installed)
if (!require("devtools")) install.packages("devtools")
devtools::install_github("ZhuMetLab/MrnAnnoAlgo3")Demo data is available on the MetDNA webserver (http://metdna.zhulab.cn).
- 🐛 Bug Reports & Feature Requests: GitHub Issues
- 📧 Direct Contact: zhanghs@sioc.ac.cn
- 💬 Community Forum: MetDNA3 Discussions (Coming Soon)
- 💬 QQ Group (for Chinese users): 927406473
If you use MetDNA3 in your research, please cite: (Coming Soon)
- MetDNA2: https://github.com/ZhuMetLab/MetDNA2
This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).
See LICENSE for details.
