# HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing

## TL;DR

HAlign-II is a scalable, efficient tool leveraging distributed computing for ultra-large biological sequence alignment and phylogenetic tree reconstruction, outperforming existing methods in speed, memory efficiency, and usability.

## Contribution

This paper introduces HAlign-II, a novel distributed computing-based tool that significantly improves ultra-large sequence alignment and phylogenetic analysis performance.

## Key findings

- Efficiently handles ultra-large biological sequences for MSA and phylogenetic tree construction.
- Exhibits high memory efficiency and scalability with increased computing resources.
- Provides a user-friendly web interface based on distributed computing infrastructure.

## Abstract

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. After comparing with most available state-of-the-art methods, our experimental results indicate the following: 1) HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large biological sequences; 2) HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource; 3) HAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

---
Source: https://tomesphere.com/paper/1704.00878