talenWF 0.1.1

Modern TALEN window finder compatible with MitoEdit. Made as a part of the St. Jude KIDS25 BioHackathon Project. This tool is an effort to revamp and modernize the TAL Effector-Nucleotide Targeter (TALE-NT) 2.0 (Doyle et al., 2012, Nucleic Acids Research)

talenWF

A minimal TALEN window finder packaged for CLI and API use, intended to be a drop-in for MitoEdit's TAL finding functionality.

Features

• 🔍 TALEN Window Finding: Efficiently finds TALEN binding sites in DNA sequences
• 🐍 Python API: Easy-to-use class-based interface
• 💻 Command Line Interface: Ready-to-use CLI tool
• 🔄 MitoEdit Compatible: Drop-in replacement for MitoEdit's TAL finding functionality
• 📊 Pandas Integration: Returns results as DataFrames for easy analysis
• 🧬 BioPython Support: Robust FASTA file handling
• ⚡ Memory Efficient: Generator-based processing for large sequences

Installation

From PyPI (recommended)

pip install talenWF

From source (development)

git clone https://github.com/yourusername/talenWF.git
cd talenWF
pip install -e .

With development dependencies

pip install talenWF[dev]

CLI

talenWF-findtal --fasta /path/to/seq.fasta --min 14 --max 18 --arraymin 14 --arraymax 18 --outpath /tmp/talenWF.tsv

API

from talenWF import FindTALTask

# Using the modern class-based API
task = FindTALTask(
    fasta="/path/to/seq.fasta",
    min_spacer=14,
    max_spacer=18,
    array_min=14,
    array_max=18,
    outpath="/tmp/talenWF.tsv"
)
df = task.run()

Citation

If you use talenWF in your research, please cite the original TALE-NT 2.0 tool:

Doyle, E. L., Booher, N. J., Standage, D. S., Voytas, D. F., Brendel, V. P., VanDyk, J. K., & Bogdanove, A. J. (2012). 
TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction. 
Nucleic Acids Research, 40(W1), W117-W122. https://doi.org/10.1093/nar/gks608

About This Project

talenWF is a modernized implementation of the TALE-NT 2.0 algorithm, developed as part of the St. Jude KIDS25 BioHackathon Project. This tool provides a Python-based, memory-efficient alternative to the original TALE-NT 2.0 web interface, with improved performance and easier integration into bioinformatics workflows.

Key Improvements:

• Modern Python implementation with class-based API
• Memory-efficient generator-based processing
• Command-line interface for batch processing
• Pandas integration for data analysis
• BioPython support for robust sequence handling

License

This project is licensed under the MIT License - see the LICENSE file for details.