Metadata-Version: 1.2
Name: metabolinks
Version: 0.61
Summary: A set of tools for high-resolution MS metabolomics data analysis
Home-page: https://github.com/aeferreira/metabolinks
Author: António Ferreira
Author-email: aeferreira@fc.ul.pt
Maintainer: António Ferreira
Maintainer-email: aeferreira@fc.ul.pt
License: MIT
Download-URL: https://github.com/aeferreira/metabolinks
Description: 
        ***********
        Metabolinks
        ***********
        
        ``Metabolinks`` is a Python package that provides a set of tools for high-resolution
        MS metabolomics data analysis.
                
        Metabolinks aims at providing several tools that streamline most of
        the metabolomics workflow. These tools were written having ultra-high
        resolution MS based metabolomics in mind.
        
        Features are a bit scarce right now:
        
        - peak list alignment
        - data matrix preprocessing, and similarity measures
        - compound taxonomy retrieval
        
        But our road map is clear and we expect to stabilize in a beta version pretty soon.
        
        Stay tuned, and check out the examples folder (examples are provided as
        jupyter notebooks).
        
        Installing
        ==========
        
        ``Metabolinks`` is distributed on PyPI_ and can be installed with pip on
        a Python 3.6+ installation::
        
           pip install metabolinks
        
        .. _PyPI: https://pypi.org/project/metabolinks
        
        
        However, even if ``Metabolinks`` is written in Python, it requires some of the powerful scientific
        packages that are pre-installed on "Scientific/Data Science Python" distributions.
        
        One of these two products is highly recommended:
        
        - `Anaconda <https://store.continuum.io/cshop/anaconda/>`_ (or `Miniconda <http://conda.pydata.org/miniconda.html>`_ followed by the necessary ``conda install``'s)
        - `Enthought Canopy <https://www.enthought.com/products/canopy/>`_
        
        The formal requirements are:
        
        - Python 3.6 and above
        - ``setuptools``, ``pip``, ``six``, ``requests`` and ``pytest``
        - ``numpy``, ``scipy``, ``matplotlib``, ``pandas`` and ``scikit-learn``
        
        The installation of the ``Jupyter`` platform is also recommended since
        the examples are provided as *Jupyter notebooks*.
        
        
Keywords: Metabolomics,Mass Spectrometry,Data Analysis,Ultra-high resolution MS
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
