| Name | xomics JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | |
| Summary | Python framework for eXplainable Omics analysis |
| upload_time | 2023-10-11 22:35:10 |
| maintainer | |
| docs_url | None |
| author | Stephan Breimann |
| requires_python | >=3.9,<=3.11 |
| license | MIT |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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No Travis.
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No coveralls.
|
Welcome to the xOmics documentation
===================================
.. Developer Notes:
Please update badges in README.rst and vice versa
.. image:: https://github.com/breimanntools/xomics/workflows/Build/badge.svg
:target: https://github.com/breimanntools/xomics/actions
:alt: Build Status
.. image:: https://github.com/breimanntools/xomics/workflows/Python-check/badge.svg
:target: https://github.com/breimanntools/xomics/actions
:alt: Python-check
.. image:: https://img.shields.io/pypi/status/xomics.svg
:target: https://pypi.org/project/xomics/
:alt: PyPI - Status
.. image:: https://img.shields.io/pypi/pyversions/xomics.svg
:target: https://pypi.python.org/pypi/xomics
:alt: Supported Python Versions
.. image:: https://img.shields.io/pypi/v/xomics.svg
:target: https://pypi.python.org/pypi/xomics
:alt: PyPI - Package Version
.. image:: https://anaconda.org/conda-forge/xomics/badges/version.svg
:target: https://anaconda.org/conda-forge/xomics
:alt: Conda - Package Version
.. image:: https://readthedocs.org/projects/xomics/badge/?version=latest
:target: https://xomics.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://img.shields.io/github/license/breimanntools/xomics.svg
:target: https://github.com/breimanntools/xomics/blob/master/LICENSE
:alt: License
.. image:: https://pepy.tech/badge/xomics
:target: https://pepy.tech/project/xomics
:alt: Downloads
**xOmics** (eXplainable Omics) is a Python framework developed for streamlined and explainable omics analysis, with a
spotlight on differential proteomics expression data. It introduces the following key algorithms:
- **cImpute**: Conditional Imputation - A transparent method for hybrid missing value imputation.
- **xOmicsIntegrate**: Protein-centric integration of multiple (prote)omic datasets to find commonalities and differences.
- **xOmicsRank**: Protein-centric ranking of (prote)omic data, leveraging functional enrichment results.
In addition, **xOmics** provides functional capabilities for efficiently loading benchmark proteomics datasets via
**load_datasets**, accompanied by corresponding enrichment data.A suite of supportive functions is also available to
facilitate a smooth and efficient (prote)omic analysis pipeline.
Install
=======
**xOmics** can be installed either from `PyPi <https://pypi.org/project/xomics>`_ or
`conda-forge <https://anaconda.org/conda-forge/xomics>`_:
.. code-block:: bash
pip install -u xomics
or
conda install -c conda-forge xomics
Contributing
============
We appreciate bug reports, feature requests, or updates on documentation and code. For details, please refer to
`Contributing Guidelines <CONTRIBUTING.rst>`_. For further questions or suggestions, please email stephanbreimann@gmail.com.
Citations
=========
If you use xOmics in your work, please cite the respective publication as follows:
**xOmics**:
[Citation details and link if available]
**cImpute**:
[Citation details and link if available]
**xOmicsIntegrate**:
[Citation details and link if available]
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