fastHaN

fastHaN constructs haplotype networks from large-sample DNA sequence datasets to enable rapid inference of genealogical relationships for population genetics, molecular ecology, epidemiology, and evolutionary studies.

Key Features:

• Efficiency: For datasets with haplotype lengths of 30 kilobases (kb), the Median Joining Network (MJN) implementation in fastHaN is 3,000 times faster than PopART and 70 times faster than NETWORK in single-threaded mode.
• Scalability: fastHaN supports multi-threaded processing to handle large datasets and high-throughput genomic analyses.
• Algorithm Implementation: fastHaN implements both the Median Joining Network (MJN) and the Templeton-Crandall-Sing (TCS) algorithms; the TCS implementation is 100 times faster than PopART and 5,800 times faster than the standalone TCS software.

Scientific Applications:

• Population Genetics: Constructing haplotype networks to explore genealogical relationships, genetic diversity, and population structure.
• Molecular Ecology and Epidemiology: Facilitating analyses of how genetic variation influences ecological interactions and pathogen spread.
• Evolutionary Studies: Mapping genealogical connections among DNA sequences to elucidate evolutionary histories.

Methodology:

Implements the Median Joining Network (MJN) and Templeton-Crandall-Sing (TCS) algorithms, supports single-threaded and multi-threaded execution, and includes optimizations for computational speed and accuracy.