Table of Contents

• Introduction

  • MetaMS
  • Version
  • Data Input
  • Data Output
  • Data Structure
  • Features
  • Code Documentation

• Installation

  • PyPi

• Execution:

  • CLI
  • MiniWDL
  • Docker Container

MetaMS

MetaMS is a workflow for metabolomics data processing and annotation

Current Version

2.2.3

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
• m/z based Chromatogram Peak Deconvolution,
• Manual and automatic noise threshold calculation
• First and second derivatives peak picking methods
• Peak Area Calculation

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

Make sure you have python 3.9.13 installed before continue

• 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   

Execution

metaMS dump_toml_template metams.toml

metaMS dump_corems_toml_template corems.toml

Modify the metams.toml and corems.toml accordingly to your dataset and workflow parameters make sure to include corems.json path inside the metams.toml: "corems_toml_path": "path_to_corems.toml"

metaMS run-gcms-workflow path_to_metams.toml

MiniWDL

Make sure you have python 3.9.13 installed before continue

MiniWDL uses the microbiome/metaMS image so there is not need to install metaMS

• Change wdl/metams_input.json to specify the data location

• Change data/corems.toml to specify the workflow parameters

Install miniWDL:

pip3 install miniwdl

Call:

miniwdl run wdl/metaMS.wdl -i wdl/metams_input.json --verbose --no-cache --copy-input-files

MetaMS Docker Container

You will need docker and docker compose:

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

• Pull from Docker Registry:

  docker pull microbiomedata/metams:latest
  

• or Build the image from source:

  docker build -t microbiomedata/metams:latest .

• Run Workflow from Container:

  $(data_dir) = full path of directory containing the gcms data $(config_dir) = full path of directory containing configuration and parameters metams.toml and corems.toml

  docker run -v $(data_dir):/metaB/data -v $(config_dir):/metaB/configuration microbiomedata/metams:latest metaMS run-gcms-workflow /metaB/configuration/metams.toml

• Getting the parameters templates:

  docker run -v $(config_dir):/metaB/configuration microbiomedata/metams:latest metaMS dump-json-template /metaB/configuration/metams.toml

  docker run -v $(config_dir):/metaB/configuration microbiomedata/metams:latest metaMS dump-corems-json-template /metaB/configuration/corems.toml

Disclaimer

This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor Battelle, nor any of their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights.

Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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               UNITED STATES DEPARTMENT OF ENERGY
                under Contract DE-AC05-76RL01830