Metadata-Version: 2.1
Name: metaMS
Version: 2.0.3
Summary: Data processing, and annotation for metabolomics analysis by low-resolution GC-MS
Home-page: https://github.com/EMSL-Computing/MetaMS
Author: Corilo, Yuri
Author-email: corilo@pnnl.gov
License: BSD
Description: # Table of Contents  
        - Introduction
          - [MetaMS](#MetaMS)  
          - [Version](#current-version)  
          - [Data Input](#data-input-formats)  
          - [Data Output](#data-output-formats)  
          - [Data Structure](#data-structure-types)  
          - [Features](#available-features)  
        - Installation
          - [PyPi](#metams-installation)  
        - Execution:  
          - [CLI](#execution)  
          - [MiniWDL](#MiniWDL)  
          - [Docker Container](#metams-docker-container)  
        # MetaMS
        
        **MetaMS** is a workflow for metabolomics data processing and annotation
        
        ## Current Version
        
        ### `2.0.3`
        
        ### 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
        
        - PyPi:     
        ```bash
        pip3 install metams
        ```
        
        - From source:
         ```bash
        pip3 install --editable .
        ```
        
        To be able to open chemstation files a installation of pythonnet is needed:
        - Windows: 
            ```bash
            pip3 install pythonnet
            ```
        
        - Mac and Linux:
            ```bash
            brew install mono
            pip3 install pythonnet   
            ```
        
        ## Execution
        
        ```bash
        metaMS dump_json_template MetamsFile.json
        ```
        ```bash
        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" 
        
        ```bash
        metaMS run-gcms-workflow path_to_MetamsFile.json
        ```
        
        ## MiniWDL 
        - Change wdl/metams_input.json to specify the data location
        
        - Change data/CoremsFile.json to specify the workflow parameters
        
        Install miniWDL:
        ```bash
        pip3 install miniwdl
        ```
        
        Call:
        ```bash
        miniwdl run wdl/metaMS.wdl -i wdl/metams_input.json --verbose --no-cache --copy-input-files
        ```
        ## MetaMS Docker Container
        
        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](https://hub.docker.com/?overlay=onboarding)
        
        - Pull from Docker Registry:
        
            ```bash
            docker pull corilo/metams:latest
            
            ```
        - or Build the image from source:
        
            ```bash
            docker build -t metams:latest .
            ```
        - Run Workflow from Container:
        
            $(data_dir) = full path of directory containing the gcms data, MetamsFile.json and CoremsFile.json
            
            ```bash
            docker run -v $(data_dir):/metaB/data corilo/metams:latest metaMS run-gcms-workflow /metaB/data/MetamsFile.json
            ```
        
        - Getting the parameters templates:
            
            ```bash
            docker run -v $(data_dir):/metaB/data corilo/metams:latest metaMS dump_json_template /metaB/data/MetamsFile.json
            ```
            
            ```bash
            docker run -v $(data_dir):/metaB/data corilo/metams:latest metaMS dump_corems_json_template /metaB/data/CoremsFile.json
            ```
        
        ## 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.
        
                         PACIFIC NORTHWEST NATIONAL LABORATORY
                                      operated by
                                        BATTELLE
                                        for the
                           UNITED STATES DEPARTMENT OF ENERGY
                            under Contract DE-AC05-76RL01830
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
