Metadata-Version: 2.4
Name: pyTax4Fun2
Version: 1.2.1
Summary: A Python Implementation of pyTax4Fun2 for Functional Profiling and Redundancy Analysis of Bacterial Communities via 16S rRNA Gene Sequences, Featuring Polars for Efficient Processing of Large Genomic Datasets
Home-page: https://gitlab.com/biomikalab/pyTax4Fun2
Author: Maulana Malik Nashrulloh
Author-email: maulana@genbinesia.or.id
Project-URL: Documentation, https://gitlab.com/biomikalab/pyTax4Fun2
Project-URL: Source Code, https://gitlab.com/biomikalab/pyTax4Fun2
Project-URL: Bug Tracker, https://gitlab.com/biomikalab/pyTax4Fun2/issues
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Development Status :: 5 - Production/Stable
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: polars[rt64]==1.39.3
Requires-Dist: polars-bio==0.26.0
Requires-Dist: numpy==2.3.5
Requires-Dist: scipy>=1.16.3
Requires-Dist: scikit-learn>=1.8.0
Requires-Dist: scikit-bio>=0.7.2
Requires-Dist: ete3>=3.1.3
Requires-Dist: tinydb==4.8.2
Requires-Dist: pbr>=7.0.3
Requires-Dist: stevedore>=5.6.0
Requires-Dist: cogent3>=2026.1.20a1
Requires-Dist: biopython>=1.86
Requires-Dist: requests
Requires-Dist: tqdm
Requires-Dist: loguru>=0.7.3
Requires-Dist: umap-learn>=0.5.11
Requires-Dist: pyyaml>=6.0.3
Requires-Dist: matplotlib>=3.10.8
Requires-Dist: seaborn>=0.13.2
Requires-Dist: networkx>=3.6.1
Requires-Dist: statsmodels>=0.14.6
Requires-Dist: psutil>=7.0.0
Requires-Dist: numba>=0.64.0
Requires-Dist: legacy-cgi>=2.6.4
Requires-Dist: adjustText==1.3.0
Requires-Dist: alphashape==1.3.1
Requires-Dist: shapely==2.1.2
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# pyTax4Fun2

![Python Version](https://img.shields.io/badge/python-3.11+-blue.svg)
![License: GPL v3](https://img.shields.io/badge/License-AGPLv3-blue.svg)
![Version](https://img.shields.io/badge/version-1.2.1-green.svg)

A Python Implementation of Tax4Fun2 for Functional Profiling and Redundancy Analysis of Bacterial Communities via 16S rRNA Gene Sequences, Featuring Polars for Efficient Processing of Large Genomic Datasets, with Extra Statistical Analysis Support for Alpha and Beta Diversity

# Authors
- Ninda Rachmadani (Department of Biology, Faculty of Matehematics and Natural Sciences,Brawijaya University)
- Maulana Malik Nashrulloh (Division of Biomics Research, Department of Sciences, Generasi Biologi Indonesia Foundation)
- Irfan Mustafa (Department of Biology, Faculty of Matehematics and Natural Sciences,Brawijaya University)
- Brian Rahardi (Department of Bioinformatics, Faculty of Mathematics and Natural Sciences, Brawijaya University) 
- Choirul Ainiyati (Division of Biomics Research, Department of Sciences, Generasi Biologi Indonesia Foundation)
- Khalid Hafazallah (Division of Ecology and Conservation, Department of Sciences, Generasi Biologi Indonesia Foundation)
- Reza Raihandhany (Division of Botany, Department of Sciences, Generasi Biologi Indonesia Foundation)
- Muhammad Badrut Tamam (Division of Biomics Research, Department of Sciences, Generasi Biologi Indonesia Foundation)

# Quick Start

## Dependencies

Make sure that your system have Python >=3.11 installed and these packages/libraries installed:

- polars[rt64]==1.39.3
- polars-bio==0.26.0
- pandas==2.3.3
- numpy==2.3.5
- scipy==1.16.3
- scikit-learn==1.8.0
- scikit-bio==0.7.2
- ete3==3.1.3
- tinydb==4.8.2
- pbr==7.0.3
- stevedore==5.7.0
- cogent3==2026.1.20a1
- biopython==1.86
- requests==2.33.1
- tqdm==4.67.3
- loguru==0.7.3
- umap-learn==0.5.11
- pyyaml==6.0.3
- matplotlib==3.10.8
- seaborn==0.13.2
- networkx==3.6.1
- statsmodels==0.14.6
- psutil==7.0.0
- numba==0.64.0
- legacy-cgi==2.6.4
- adjustText==1.3.0
- alphashape==1.3.1
- shapely==2.1.2


## Installation
Currently we only support installation thru `pip` command only.

```bash
pip install pyTax4Fun2
```

We recommend you to install pyTax4Fun2 in an isolated conda environment, e.g. `my_pyTax4Fun2`. While we use Python>=3.11, we recommend you to use latest Python 3.14 for much better support. Please install these programs 

```bash
conda create -n my_pyTax4Fun2 python=3.14
conda install anaconda::pyarrow==22.0.0
conda install conda-forge::uproc
conda install bioconda::blast diamond prodigal vsearch
pip install pyTax4Fun2
```

# Acknowledgments
- This program was made as part of research mini-project "PyTax4Fun2: A Python Tool for Functional Profiling and Redundancy Analysis of Bacterial Communities via 16S rRNA Gene Sequences, Featuring Polars for Efficient Processing of Large Genomic Datasets" (Project #BIOMIKA-02), funded internally by Generasi Biologi Indonesia Foundation.
- The collaboration project between Generasi Biologi Indonesia Foundation and Faculty of Mathematics and Natural Sciences Brawijaya University was made possible thru the Cooperation Agreement No. 05.294/Genbinesia/I/2026 and No. 00818/DST/UN10.F0901/B/KS/2026.
- Ninda Rachmadani was supported by Generasi Biologi Indonesia Foundation Undergraduate Thesis Assistance Program thru Contract No. 01.297/Genbinesia/IV/2026.

# Citation
A dedicated publication for this program is not yet available. For citation purposes, please refer to the following technical reports and theses:

- Nashrulloh, M.M., Rahardi, B. (2026). *pyTax4Fun2: A Python Tool for Functional Profiling and Redundancy Analysis of Bacterial Communities via 16S rRNA Gene Sequences, Featuring Polars for Efficient Processing of Large Genomic Datasets—I: Initial Development* (Technical Report No. GBR-TR-BIOMIKA-02/Genbinesia/I/2026). Generasi Biologi Indonesia Foundation. Gresik, Indonesia.

- Rachmadani, N., Nashrulloh, M.M., Mustafa, I., Rahardi, B., Ainiyati, C., Hafazallah, K., Raihandhany, R., Tamam, Mh.B. (2026). *pyTax4Fun2: A Python Tool for Functional Profiling and Redundancy Analysis of Bacterial Communities via 16S rRNA Gene Sequences, Featuring Polars for Efficient Processing of Large Genomic Datasets—II: Further Development (On Alpha Diversity and Beta Diversity)* (Technical Report No. GBR-TR-BIOMIKA-04/Genbinesia/III/2026). Generasi Biologi Indonesia Foundation. Gresik, Indonesia.

- Rachmadani, N. (2026). *Komparasi analisis fungsional komunitas bakteri berbasis sekuen gen 16S rRNA menggunakan pyTax4Fun2 dan Tax4Fun2*. Undergraduate Thesis. Departemen Biologi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Brawijaya. Malang, Indonesia. [in Indonesian].

If you wish to cite this repository, you may use the following APA-style reference entry:

Rachmadani, N., Nashrulloh, M.M., Mustafa, I., Rahardi, B., Ainiyati, C., Hafazallah, K., Raihandhany, R., Tamam, Mh.B. (2026). pyTax4Fun2: A Python Implementation of pyTax4Fun2 for Functional Profiling and Redundancy Analysis of Bacterial Communities via 16S rRNA Gene Sequences, Featuring Polars for Efficient Processing of Large Genomic Datasets (Version 1.2.1) [Computer software]. https://gitlab.com/biomikalab/pytax4fun2

# License
This project is licensed under the GNU Affero General Public License v3.0 - See the LICENSE file for details.
