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        "author": "Daniel Domingo-Fern\u00e1ndez",
        "author_email": "danieldomingofernandez@hotmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
        ],
        "description": "PathwayForte |build| |docs| |coverage| |zenodo|\n===============================================\nA Python package for benchmarking pathway databases with functional enrichment and prediction methods\ntasks.\n\nInstallation |pypi_version| |python_versions| |pypi_license|\n------------------------------------------------------------\n``pathway_forte`` can be installed from `PyPI <https://pypi.org/project/pathway-forte>`_\nwith the following command in your terminal:\n\n.. code-block:: sh\n\n    $ python3 -m pip install pathway_forte\n\nThe latest code can be installed from `GitHub <https://github.com/pathwayforte/pathway-forte>`_\nwith:\n\n.. code-block:: sh\n\n    $ python3 -m pip install git+https://github.com/pathwayforte/pathway-forte.git\n\nFor developers, the code can be installed with:\n\n.. code-block:: sh\n\n    $ git clone https://github.com/pathwayforte/pathway-forte.git\n    $ cd pathway-forte\n    $ python3 -m pip install -e .\n\nMain Commands\n-------------\n\nThe table below lists the main commands of PathwayForte.\n\n+------------+--------------------------------+\n| Command    | Action                         |\n+============+================================+\n| datasets   | Lists of Cancer Datasets       |\n+------------+--------------------------------+\n| export     | Export Gene Sets using ComPath |\n+------------+--------------------------------+\n| ora        | List of ORA Analyses           |\n+------------+--------------------------------+\n| fcs        | List of FCS Analyses           |\n+------------+--------------------------------+\n| prediction | List of Prediction Methods     |\n+------------+--------------------------------+\n\nFunctional Enrichment Methods\n-----------------------------\n\n- **ora**. Lists Over-Representation Analyses (e.g., one-tailed hyper-geometric test).\n\n- **fcs**. Lists Functional Class Score Analyses such as GSEA and ssGSEA using `GSEAPy <https://github.com/ostrokach/gseapy>`_.\n\n   \nPrediction Methods\n------------------\n``pathway_forte`` enables three classification methods (i.e., binary classification, training SVMs for multi-classification tasks, or survival analysis) using individualized pathway activity scores. The scores can be calculated from any pathway with a variety of tools (see [1]_) using any pathway database that enables to export its gene sets.\n\n- **binary**. Trains an elastic net model for a binary classification task (e.g., tumor vs. normal patients). The training is conducted using a nested cross validation approach (the number of cross validation in both loops can be selected). The model used can be easily changed since most of the models in `scikit-learn <https://scikit-learn.org/>`_ (the machine learning library used by this package) required the same input.\n\n- **subtype**. Trains a SVM model for a multi-class classification task (e.g., predict tumor subtypes). The training is conducted using a nested cross validation approach (the number of cross validation in both loops can be selected). Similarly as the previous classification task, other models can quickly be implemented.\n\n- **survival**. Trains a Cox's proportional hazard's model with elastic net penalty. The training is conducted using a nested cross validation approach with a grid search in the inner loop. This analysis requires pathway activity scores, patient classes and lifetime patient information.\n\nOther\n-----\n\n- **export**. Export GMT files with current gene sets for the pathway databases included in ComPath [2]_.\n\n- **datasets**. Lists the TCGA data sets [3]_ that are ready to run in ``pathway_forte``.\n\nReferences\n----------\n\n.. [1] Lim, S., *et al.* (2018). `Comprehensive and critical evaluation of individualized pathway activity measurement tools on pan-cancer data <https://doi.org/10.1093/bib/bby097>`_. *Briefings in bioinformatics*, bby125.\n\n.. [2] Domingo-Fern\u00e1ndez, D., *et al.* (2018). `ComPath: An ecosystem for exploring, analyzing, and curating mappings across pathway databases <https://doi.org/10.1038/s41540-018-0078-8>`_. *npj Syst Biol Appl.*, 4(1):43.\n\n.. [3] Weinstein, J. N., *et al.* (2013). `The cancer genome atlas pan-cancer analysis project <https://doi.org/10.1038/ng.2764>`_. *Nature genetics*, 45(10), 1113.\n\n\n.. |build| image:: https://travis-ci.com/pathwayforte/pathway-forte.svg?branch=master\n    :target: https://travis-ci.com/pathwayforte/pathway-forte\n    :alt: Build Status\n\n.. |docs| image:: http://readthedocs.org/projects/pathwayforte/badge/?version=latest\n    :target: https://pathwayforte.readthedocs.io/en/latest/\n    :alt: Documentation Status\n\n.. |coverage| image:: https://codecov.io/gh/pathwayforte/pathway-forte/coverage.svg?branch=master\n    :target: https://codecov.io/gh/pathwayforte/pathway-forte?branch=master\n    :alt: Coverage Status\n\n.. |python_versions| image:: https://img.shields.io/pypi/pyversions/pathway_forte.svg\n    :target: https://pypi.org/project/pathway-forte\n    :alt: Stable Supported Python Versions\n\n.. |pypi_version| image:: https://img.shields.io/pypi/v/pathway_forte.svg\n    :target: https://pypi.org/project/pathway-forte\n    :alt: Current version on PyPI\n\n.. |pypi_license| image:: https://img.shields.io/pypi/l/pathway_forte.svg\n    :target: https://github.com/pathwayforte/pathway-forte/blob/master/LICENSE\n    :alt: Apache-2.0\n\n.. |zenodo| image:: https://zenodo.org/badge/178654585.svg\n    :target: https://zenodo.org/badge/latestdoi/178654585",
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