Powerful, Simple, and Fast
DNAAT is designed for bioinformaticians, students, and researchers who need a straightforward tool for sequence analysis without the overhead of heavy software. By implementing core algorithms in C, DNAAT offers significant performance gains over pure Python implementations.
Core Features
- Global Alignment (Needleman-Wunsch): Ideal for comparing two sequences of similar lengths from end to end.
- Local Alignment (Smith-Waterman): Perfect for finding the most similar sub-regions between two sequences.
- Affine Gap Penalties: Biologically accurate scoring that distinguishes between gap opening and extension.
- C-Accelerated Performance: Critical functions are written in C for maximum speed, with a simple Python wrapper for ease of use.
- Cross-Platform: Runs seamlessly on Windows, Linux, and macOS.
- Visualization: Generate and view alignment score grids and optimal alignment paths with Matplotlib.
Get Started in Minutes
Ready to align some sequences? Visit the Usage Guide to get started, or dive into the code on GitHub to see how it works.