Welcome to the AAanalysis documentation!
========================================
..
Developer Notes:
Please make sure that badges in badges.rst (Read The Docs)
and README.rst (GitHub) are the same.
.. Group 1: Package badges
.. |PyPI Status| image:: https://img.shields.io/pypi/status/aaanalysis.svg
:target: https://pypi.org/project/aaanalysis/
:alt: PyPI - Status
.. |PyPI Version| image:: https://img.shields.io/pypi/v/aaanalysis.svg
:target: https://pypi.python.org/pypi/aaanalysis
:alt: PyPI - Package Version
.. |Supported Python Versions| image:: https://img.shields.io/pypi/pyversions/aaanalysis.svg
:target: https://pypi.python.org/pypi/aaanalysis
:alt: Supported Python Versions
.. |Downloads| image:: https://pepy.tech/badge/aaanalysis
:target: https://pepy.tech/project/aaanalysis
:alt: Downloads
.. |License| image:: https://img.shields.io/github/license/breimanntools/aaanalysis.svg
:target: https://github.com/breimanntools/aaanalysis/blob/master/LICENSE
:alt: License
.. Group 2: Testing badges
.. |Unit Tests| image:: https://github.com/breimanntools/aaanalysis/actions/workflows/main.yml/badge.svg
:target: https://github.com/breimanntools/aaanalysis/actions/workflows/main.yml
:alt: CI/CD Pipeline
.. |CodeQL| image:: https://github.com/breimanntools/aaanalysis/actions/workflows/codeql_analysis.yml/badge.svg
:target: https://github.com/breimanntools/aaanalysis/actions/workflows/codeql_analysis.yml
:alt: CodeQL
.. |Codecov| image:: https://codecov.io/gh/breimanntools/aaanalysis/branch/master/graph/badge.svg
:target: https://codecov.io/gh/breimanntools/aaanalysis
:alt: Codecov
.. |Documentation Status| image:: https://readthedocs.org/projects/aaanalysis/badge/?version=latest
:target: https://aaanalysis.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. Group 3: Potential badges for future
.. |Conda Version| image:: https://anaconda.org/conda-forge/aaanalysis/badges/version.svg
:target: https://anaconda.org/conda-forge/aaanalysis
:alt: Conda - Package Version
..
Missing badges
|Conda Version|
.. list-table::
:widths: 20 80
:header-rows: 1
* - **Package**
- |PyPI Status| |PyPI Version| |Supported Python Versions| |Downloads| |License|
* - **Testing**
- |Unit Tests| |CodeQL| |Codecov| |Documentation Status|
**AAanalysis** (Amino Acid analysis) is a Python framework for interpretable sequence-based protein prediction.
Its foundation are the following algorithms:
- **CPP**: Comparative Physicochemical Profiling, a feature engineering algorithm comparing two sets of protein
sequences to identify the set of most distinctive features.
- **dPULearn**: deterministic Positive-Unlabeled (PU) Learning algorithm to enable training on
unbalanced and small datasets.
- **AAclust**: k-optimized clustering wrapper framework to select redundancy-reduced sets of numerical scales
(e.g., amino acid scales).
In addition, AAanalysis provide functions for loading various protein benchmark datasets, amino acid scales,
and their two-level classification (**AAontology**). We combined **CPP** with the explainable
AI `SHAP <https://shap.readthedocs.io/en/latest/index.html>`_ framework to explain sample level predictions with
single-residue resolution.
If you are looking to make publication-ready plots with a view lines of code, see our
`Plotting Prelude <https://aaanalysis.readthedocs.io/en/latest/generated/plotting_prelude.html>`_.
You can find the official documentation at `Read the Docs <https://aaanalysis.readthedocs.io/en/latest/>`_.
Install
=======
**AAanalysis** can be installed from `PyPi <https://pypi.org/project/aaanalysis>`_:
.. code-block:: bash
pip install aaanalysis
For extended features, including our explainable AI module, please use the 'professional' version:
.. code-block:: bash
pip install aaanalysis[pro]
Contributing
============
We appreciate bug reports, feature requests, or updates on documentation and code. For details, please refer to
`Contributing Guidelines <CONTRIBUTING.rst>`_. These include specifics about AAanalysis and also notes on Test
Guided Development (TGD) using ChatGPT. For further questions or suggestions, please email stephanbreimann@gmail.com.
Citations
=========
If you use AAanalysis in your work, please cite the respective publication as follows:
**AAclust**:
Breimann and Frishman (2024a),
*AAclust: k-optimized clustering for selecting redundancy-reduced sets of amino acid scales*,
`bioRxiv <https://www.biorxiv.org/content/10.1101/2024.02.04.578800v1>`__.
**AAontology**:
Breimann *et al.* (2024b),
*AAontology: An ontology of amino acid scales for interpretable machine learning*,
`bioRxiv <https://www.biorxiv.org/content/10.1101/2023.08.03.551768v1>`__.
**CPP**:
Breimann and Kamp *et al.* (2024c),
*Charting γ-secretase substrates by explainable AI*, .. # Link if available
**dPULearn**:
Breimann and Kamp *et al.* (2024c),
*Charting γ-secretase substrates by explainable AI*, .. # Link if available
Raw data
{
"_id": null,
"home_page": "https://aaanalysis.readthedocs.io",
"name": "aaanalysis",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.9",
"maintainer_email": null,
"keywords": "protein, prediction, bioinformatics, machine learning, interpretable AI",
"author": "Stephan Breimann",
"author_email": "stephanbreimann@gmail.de",
"download_url": "https://files.pythonhosted.org/packages/84/eb/560a4451a9e2f503fa59a0b2e9999072babca6a723d641a67c5807a9bc63/aaanalysis-1.0.0.tar.gz",
"platform": null,
"description": "Welcome to the AAanalysis documentation!\n========================================\n..\n Developer Notes:\n Please make sure that badges in badges.rst (Read The Docs)\n and README.rst (GitHub) are the same.\n\n.. Group 1: Package badges\n.. |PyPI Status| image:: https://img.shields.io/pypi/status/aaanalysis.svg\n :target: https://pypi.org/project/aaanalysis/\n :alt: PyPI - Status\n\n.. |PyPI Version| image:: https://img.shields.io/pypi/v/aaanalysis.svg\n :target: https://pypi.python.org/pypi/aaanalysis\n :alt: PyPI - Package Version\n\n.. |Supported Python Versions| image:: https://img.shields.io/pypi/pyversions/aaanalysis.svg\n :target: https://pypi.python.org/pypi/aaanalysis\n :alt: Supported Python Versions\n\n.. |Downloads| image:: https://pepy.tech/badge/aaanalysis\n :target: https://pepy.tech/project/aaanalysis\n :alt: Downloads\n\n.. |License| image:: https://img.shields.io/github/license/breimanntools/aaanalysis.svg\n :target: https://github.com/breimanntools/aaanalysis/blob/master/LICENSE\n :alt: License\n\n.. Group 2: Testing badges\n.. |Unit Tests| image:: https://github.com/breimanntools/aaanalysis/actions/workflows/main.yml/badge.svg\n :target: https://github.com/breimanntools/aaanalysis/actions/workflows/main.yml\n :alt: CI/CD Pipeline\n\n.. |CodeQL| image:: https://github.com/breimanntools/aaanalysis/actions/workflows/codeql_analysis.yml/badge.svg\n :target: https://github.com/breimanntools/aaanalysis/actions/workflows/codeql_analysis.yml\n :alt: CodeQL\n\n.. |Codecov| image:: https://codecov.io/gh/breimanntools/aaanalysis/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/breimanntools/aaanalysis\n :alt: Codecov\n\n.. |Documentation Status| image:: https://readthedocs.org/projects/aaanalysis/badge/?version=latest\n :target: https://aaanalysis.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n\n.. Group 3: Potential badges for future\n.. |Conda Version| image:: https://anaconda.org/conda-forge/aaanalysis/badges/version.svg\n :target: https://anaconda.org/conda-forge/aaanalysis\n :alt: Conda - Package Version\n\n\n..\n Missing badges\n |Conda Version|\n\n.. list-table::\n :widths: 20 80\n :header-rows: 1\n\n * - **Package**\n - |PyPI Status| |PyPI Version| |Supported Python Versions| |Downloads| |License|\n * - **Testing**\n - |Unit Tests| |CodeQL| |Codecov| |Documentation Status|\n\n**AAanalysis** (Amino Acid analysis) is a Python framework for interpretable sequence-based protein prediction.\nIts foundation are the following algorithms:\n\n- **CPP**: Comparative Physicochemical Profiling, a feature engineering algorithm comparing two sets of protein\n sequences to identify the set of most distinctive features.\n- **dPULearn**: deterministic Positive-Unlabeled (PU) Learning algorithm to enable training on\n unbalanced and small datasets.\n- **AAclust**: k-optimized clustering wrapper framework to select redundancy-reduced sets of numerical scales\n (e.g., amino acid scales).\n\nIn addition, AAanalysis provide functions for loading various protein benchmark datasets, amino acid scales,\nand their two-level classification (**AAontology**). We combined **CPP** with the explainable\nAI `SHAP <https://shap.readthedocs.io/en/latest/index.html>`_ framework to explain sample level predictions with\nsingle-residue resolution.\n\nIf you are looking to make publication-ready plots with a view lines of code, see our\n`Plotting Prelude <https://aaanalysis.readthedocs.io/en/latest/generated/plotting_prelude.html>`_.\n\n\nYou can find the official documentation at `Read the Docs <https://aaanalysis.readthedocs.io/en/latest/>`_.\n\nInstall\n=======\n**AAanalysis** can be installed from `PyPi <https://pypi.org/project/aaanalysis>`_:\n\n.. code-block:: bash\n\n pip install aaanalysis\n\nFor extended features, including our explainable AI module, please use the 'professional' version:\n\n.. code-block:: bash\n\n pip install aaanalysis[pro]\n\nContributing\n============\nWe appreciate bug reports, feature requests, or updates on documentation and code. For details, please refer to\n`Contributing Guidelines <CONTRIBUTING.rst>`_. These include specifics about AAanalysis and also notes on Test\nGuided Development (TGD) using ChatGPT. For further questions or suggestions, please email stephanbreimann@gmail.com.\n\nCitations\n=========\nIf you use AAanalysis in your work, please cite the respective publication as follows:\n\n**AAclust**:\n Breimann and Frishman (2024a),\n *AAclust: k-optimized clustering for selecting redundancy-reduced sets of amino acid scales*,\n `bioRxiv <https://www.biorxiv.org/content/10.1101/2024.02.04.578800v1>`__.\n\n**AAontology**:\n Breimann *et al.* (2024b),\n *AAontology: An ontology of amino acid scales for interpretable machine learning*,\n `bioRxiv <https://www.biorxiv.org/content/10.1101/2023.08.03.551768v1>`__.\n\n**CPP**:\n Breimann and Kamp *et al.* (2024c),\n *Charting \u03b3-secretase substrates by explainable AI*, .. # Link if available\n\n**dPULearn**:\n Breimann and Kamp *et al.* (2024c),\n *Charting \u03b3-secretase substrates by explainable AI*, .. # Link if available\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "Python framework for interpretable protein prediction",
"version": "1.0.0",
"project_urls": {
"Documentation": "https://aaanalysis.readthedocs.io",
"Homepage": "https://aaanalysis.readthedocs.io",
"Repository": "https://github.com/breimanntools/aaanalysis"
},
"split_keywords": [
"protein",
" prediction",
" bioinformatics",
" machine learning",
" interpretable ai"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "de0eb2edf9e8fd6dc7654d4174fc65cfc611446990ef064a2a5a4b1515a47c96",
"md5": "9420db36b342d6f32daac0f56bf90de5",
"sha256": "60d9b3b4152f945f84540d47885abb8b34436dbfc2e3e3e5430e4fe5068be052"
},
"downloads": -1,
"filename": "aaanalysis-1.0.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "9420db36b342d6f32daac0f56bf90de5",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.9",
"size": 8342659,
"upload_time": "2024-07-01T22:36:53",
"upload_time_iso_8601": "2024-07-01T22:36:53.839849Z",
"url": "https://files.pythonhosted.org/packages/de/0e/b2edf9e8fd6dc7654d4174fc65cfc611446990ef064a2a5a4b1515a47c96/aaanalysis-1.0.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "84eb560a4451a9e2f503fa59a0b2e9999072babca6a723d641a67c5807a9bc63",
"md5": "796b2c9eb352304153da9753dcd62cd1",
"sha256": "c2a40bfaedb5a1d1761c8b697a24d4fb45bb6fa518d874029e7e92db28dbbff5"
},
"downloads": -1,
"filename": "aaanalysis-1.0.0.tar.gz",
"has_sig": false,
"md5_digest": "796b2c9eb352304153da9753dcd62cd1",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.9",
"size": 8280213,
"upload_time": "2024-07-01T22:37:21",
"upload_time_iso_8601": "2024-07-01T22:37:21.566948Z",
"url": "https://files.pythonhosted.org/packages/84/eb/560a4451a9e2f503fa59a0b2e9999072babca6a723d641a67c5807a9bc63/aaanalysis-1.0.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-07-01 22:37:21",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "breimanntools",
"github_project": "aaanalysis",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "aaanalysis"
}
JSON
