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Converting LC−MS-based Untargeted Metabolomics Data into Image towards Clinical Diagnosis

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MetImage

LC−MS-based Untargeted Metabolomics Data into Images towards AI-based Clinical Diagnosis

About

MetImage is a python based approach to convert LC–MS-based untargeted metabolomics data into digital images. MetImage encoded the raw LC–MS data into multi-channel images, and each image retained the characteristics of mass spectra from the raw LC–MS data. MetImage can build diagnose model by multi-channel images with deep learning model.

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Workflow

Requirements

  • Python (version~=3.8)
  • Pip (version~=22.0.3)
  • Poetry (version>=1.0.0)

Install

You can install MetImage from Github.

$ git clone https://github.com/ZhuMetLab/metimage.git

Usage

For detailed usage, please refer to manual of MetImage.

Maintainers

@Hongmiao Wang

Citation

This free open-source software implements academic research by the authors and co-workers. If you use it, please support the project by citing the appropriate journal articles.

Hongmiao Wang, Yandong Yin, and Zheng-Jiang Zhu*, Encoding LC−MS-based Untargeted Metabolomics Data into Images toward AI-Based Clinical Diagnosis, Analytical Chemistry, 2023.

License

Creative Commons License This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

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Converting LC−MS-based Untargeted Metabolomics Data into Image towards Clinical Diagnosis

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  • Python 66.0%
  • Jupyter Notebook 34.0%