pyTax4Fun2 1.2.1

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

pyTax4Fun2

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.

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

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.