A fast divide-and-conquer algorithm for indexing human genome sequences

TL;DR

This paper introduces a fast divide-and-conquer algorithm for indexing human genome sequences that significantly improves performance by reducing disk access and utilizing multi-core CPUs, outperforming previous methods.

Contribution

The proposed algorithm combines divide-and-conquer strategy with efficient disk access and parallel processing, achieving up to 3.5 times faster performance than prior algorithms.

Findings

Outperforms previous DIGEST algorithm by up to 3.5 times

Reduces random disk accesses through contiguous chunk processing

Fully utilizes multi-core CPUs for parallel genome partition processing

Abstract

Since the release of human genome sequences, one of the most important research issues is about indexing the genome sequences, and the suffix tree is most widely adopted for that purpose. The traditional suffix tree construction algorithms have severe performance degradation due to the memory bottleneck problem. The recent disk-based algorithms also have limited performance improvement due to random disk accesses. Moreover, they do not fully utilize the recent CPUs with multiple cores. In this paper, we propose a fast algorithm based on 'divide-and-conquer' strategy for indexing the human genome sequences. Our algorithm almost eliminates random disk accesses by accessing the disk in the unit of contiguous chunks. In addition, our algorithm fully utilizes the multi-core CPUs by dividing the genome sequences into multiple partitions and then assigning each partition to a different core for parallel processing. Experimental results show that our algorithm outperforms the previous fastest DIGEST algorithm by up to 3.5 times.