Metadata-Version: 2.1
Name: Augusta
Version: 1.0.6
Summary: Python package for inference of the gene regulatory network and the boolean network using RNA-Seq data.
Home-page: https://github.com/JanaMus/Augusta
Author: Jana Musilova, Zdenek Vafek, Karel Sedlar
Author-email: musilovajana@vut.cz
License: MIT
Keywords: Computational biology,Bioinformatics,RNA-Seq,mutual information,database,Boolean network,Gene Regulatory network,SBML
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.7, <3.9
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: bioinfokit
Requires-Dist: Bio<=1.79
Requires-Dist: docker
Requires-Dist: EcoNameTranslator
Requires-Dist: mygene
Requires-Dist: omnipath
Requires-Dist: urllib3>=1.26.0
Requires-Dist: requests>=2.24.0
Requires-Dist: bs4
Requires-Dist: lxml
Requires-Dist: html5lib
Requires-Dist: networkx==1.11
Requires-Dist: easydev
Requires-Dist: colormap
Requires-Dist: ccapi==0.1.0

Augusta
==========

Python package: From RNA-Seq to the Boolean Network through the Gene Regulatory Network

Documentation and tutorials are available at `augusta.readthedocs.io <https://augusta.readthedocs.io>`_.

Credits
----------------
The Augusta project is based on research detailed in the following paper. Please cite this paper when using or referencing our work:

Augusta: From RNA‐Seq to gene regulatory networks and Boolean models. Jana Musilova, Zdenek Vafek, Bhanwar Lal Puniya, Ralf Zimmer, Tomas Helikar, and Karel Sedlar. *Computational and Structural Biotechnology Journal*, 2024. DOI: `10.1016/j.csbj.2024.01.013 <https://doi.org/10.1016/j.csbj.2024.01.013>`_.


Contributors
----------------
- Jana Musilova, musilovaj22@gmail.com
- Zdenek Vafek
- Karel Sedlar, sedlar@vut.cz


Quick Guide
----------------

Dependencies:

- Python 3, versions 3.7 and 3.8
- Docker

**Installation:**

We highly recomment installing and using Augusta in a virtual environment.

.. code-block::

   $ conda create -n Augusta_venv python=3.7 anaconda
   $ conda activate Augusta_venv
   

.. code-block::

   $ pip install Augusta


**Usage:** 

See `Inputs <https://augusta.readthedocs.io/en/latest/User%20guide.html>`_ for details about input files and variables.

.. code-block:: 

   $ python
   >>> import Augusta
   
GRN and BN inference using RNA-Seq:

.. code-block:: 

   >>> Augusta.RNASeq_to_BN(count_table_input = 'MyCT_file.csv', promoter_length = My_number, genbank_file_input = 'MyGB_file.gb', normalization_type = 'My_string', motifs_max_time = My_seconds)

GRN inference using RNA-Seq:

.. code-block:: 

   >>> Augusta.RNASeq_to_GRN(count_table_input = 'MyCT_file.csv', promoter_length = My_number, genbank_file_input = 'MyGB_file.gb', normalization_type = 'My_string', motifs_max_time = My_seconds)


BN inference using GRN:

.. code-block:: 

   >>> Augusta.GRN_to_BN(GRN_input = 'MyGRN_file.csv', promoter_length = My_number, genbank_file_input = 'MyGB_file.gb', add_dbs_info = 'My_string')


GRN refinement:

.. code-block:: 

   >>> Augusta.refineGRN(GRN_input = 'MyGRN_file.csv', genbank_file_input = 'MyGB_file.gb', count_table_input = 'MyCT_file.csv', promoter_length = My_number, motifs_max_time = My_seconds)

   



