metaMS 1.0.0

Data processing, and annotation for metabolomics analysis by low-resolution GC-MS

MetaMS

MetaMS is a workflow for metabolomics data processing and annotation

Current Version

1.0.0

Data input formats

• ANDI NetCDF for GC-MS (.cdf)
• CoreMS self-containing Hierarchical Data Format (.hdf5)
• ChemStation Agilent (Ongoing)

Data output formats

• Pandas data frame (can be saved using pickle, h5, etc)
• Text Files (.csv, tab separated .txt, etc)
• Microsoft Excel (xlsx)
• JSON for workflow metadata
• Self-containing Hierarchical Data Format (.hdf5) including raw data and ime-series data-point for processed data-sets with all associated metadata stored as json attributes

Data structure types

• GC-MS

Available features

Signal Processing

• Baseline detection, subtraction, smoothing
• Manual and automatic noise threshold calculation
• First and second derivatives peak picking methods
• Peak Area Calculation
• EIC Chromatogram deconvolution(TODO)

Calibration

• Retention Index Linear XXX method

Compound Identification

• Automatic local (SQLite) or external (MongoDB or PostgreSQL) database check, generation, and search
• Automatic molecular match algorithm with all spectral similarity methods

MetaMS Installation

• PyPi:

pip3 install metams

• From source:

pip3 install --editable .

To be able to open chemstation files a installation of pythonnet is needed:

• Windows:

  pip3 install pythonnet
  

• Mac and Linux:

  brew install mono
  pip3 install pythonnet   
  

Usage

metaMS dump_json_template MetamsFile.json

metaMS dump_corems_json_template CoremsFile.json

Modify the MetamsFile.json and CoremsFile.json accordingly to your dataset and workflow parameters make sure to include CoremsFile.json path inside the MetamsFile.json: "corems_json_path": "path_to_CoremsFile.json"

metaMS run-gcms-workflow path_to_MetamsFile.json

MetaMS Docker

A docker image containing the MetaMS command line as the entry point

If you don't have docker installed, the easiest way is to install docker for desktop

• Pull from Docker Registry:

  docker pull corilo/metams:latest
  

• Build the image from source:

  docker build -t metams:latest .
  

• Run Workflow from Container:

  $(data_dir) = dir_containing the gcms data, MetamsFile.json and CoremsFile.json

  docker run -v $(data_dir):/metaB/data corilo/metams:latest run-gcms-workflow /metaB/data/MetamsFile.json    
  

• Getting the parameters templates:

  docker run -v $(data_dir):/metaB/data corilo/metams:latest dump_json_template /metaB/data/MetamsFile.json    
  

  docker run -v $(data_dir):/metaB/data corilo/metams:latest dump_corems_json_template /metaB/data/CoremsFile.json