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fastHaN: a fast and scalable program for constructing haplotype network for large-sample sequences.

Lianjiang Chi^1,2, Xiaolong Zhang^1,2,3, Yongbiao Xue^1,2,3

¹Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.

Molecular Ecology Resources

|June 26, 2023

Summary

This summary is machine-generated.

fastHaN is a new, efficient program for building DNA haplotype networks from large samples. It significantly speeds up common algorithms, making population genetics and evolutionary studies more scalable.

Keywords:

MJN algorithm TCS algorithm computational efficiency gene genealogy haplotype network multi-threaded

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Area of Science:

Genetics
Bioinformatics
Evolutionary Biology

Background:

Haplotype networks are crucial for understanding DNA sequence relationships in various biological studies.
Current computational tools face limitations with increasing sample sizes, hindering large-scale analyses.

Purpose of the Study:

To introduce fastHaN, a novel, efficient, and scalable software for constructing haplotype networks.
To address the computational challenges posed by large sample sizes in genetic and evolutionary research.

Main Methods:

Implementation of the Median Joining Network (MJN) and Templeton-Crandall-Sing (TCS) algorithms within the fastHaN framework.
Development of both single-threaded and multi-threaded modes to enhance computational performance and scalability.
Performance benchmarking against existing software like PopART and NETWORK using large datasets.

Main Results:

fastHaN demonstrates substantial speed improvements, with MJN being up to 3000x faster and TCS up to 5800x faster than existing software.
The program exhibits excellent scalability, particularly in multi-threaded mode, for handling large sample sizes.
fastHaN provides a computationally feasible solution for constructing haplotype networks from extensive DNA sequence data.

Conclusions:

fastHaN offers a significant advancement in haplotype network construction, enabling large-scale population genetics and evolutionary analyses.
The software's efficiency and scalability make it a valuable tool for researchers in molecular ecology, epidemiology, and evolutionary studies.
Accessible source code and a web-based version promote widespread adoption and application of fastHaN.