Python-2DGC

Python-2DGC

Python GCxGC-MS data processing
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. License
5. Contact

About The Project

Python package to process GCxGC-MS data.

• Processing and annotation of chromatograms
• Chromatogram visualization
• Peak tables alignment and chromatogram alignment using R package
• Machine learning and statistical analysis for the automatic detection of biomarkers
• Pixel discriminant approach for the automatic detection of biomarkers
• GCxGC-MS data simulation

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Built With

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Getting Started

This is an example of how to use the package.

Prerequisites

• Python
• Rscript
• Set NIST database location in matching_nist_lib_from_chromato_cube() in matching.py
  • Update the path to the NIST database location by setting the lib_path argument line 53
  • Set the work_dir line 55

Installation

1. Clone the repo

   git clone [email protected]:Easy47/Python-2DGC.git

2. Install Python packages

   pip install -r requirements.txt

3. R package for alignment R2DGC and RGCxGC.

If you need to simulate data

1. Generate lib scores

   cd src
   python generate_lib_scores.py

2. (Optional) Copy of the hmdb library with NIST Casno in spectra metadata (the file is already in src folder). If you need to recreate the file use the function generate_lib_scores_from_lib() in utils.py.

   import utils
   utils.generate_lib_scores_from_lib("lib_filename", "output_filename")

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Usage

1. Processes cohort chromatograms, generates peak tables and performs alignment.

   cd src
   #PATH_TO_THE_COHORT: Path to the folder containing chromatograms of the cohort.
   # OUTPUT_PATH: Directory where peak tables and aligned peak table will be generated.
   # READ detailed documentation in identification_main.py for more parameters.
   python identification_main.py -p PATH_TO_THE_COHORT -op OUTPUT_PATH

For more examples, please refer to the Documentation for an overview of the functions, read the detailed documentation of a specific function directly in its file or read example notebooks in notebooks folder.

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License

See LICENSE.txt for more information.

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Contact

• Camille Roquencourt

• Nicolas Romano

Project Link: https://github.com/Easy47/Python-2DGC

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