Adaptively Banded Smith-Waterman Algorithm for Long Reads and Its Hardware Accelerator

Yi-Lun Liao, Yu-Cheng Li, Nae-Chyun Chen, Yi-Chang Lu
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引用次数: 18

Abstract

In this paper, we propose hardware-compatible Adaptively Banded Smith-Waterman algorithm (ABSW) to align long genomic sequences. By utilizing banded Smith-Waterman algorithm to align subsequences of fixed lengths, ABSW finds alignment of a pair of arbitrarily long sequences with constant memory. In addition, a heuristic algorithm, dynamic overlapping, is proposed to make overlaps of bands of subsequences to improve accuracy. To enable hardware acceleration of ABSW, we further propose the hardware architecture of banded Smith-Waterman with traceback. Experiments show that ABSW produces near optimal alignment scores for sequences with up to 40% error rates. Our hardware implementation of ABSW demonstrates more than $\pmb{200}\times$ sneedun over software imnlementation.
长读自适应带状Smith-Waterman算法及其硬件加速
本文提出了一种硬件兼容的自适应带状Smith-Waterman算法(ABSW)来对长基因组序列进行比对。ABSW利用带状Smith-Waterman算法对固定长度的子序列进行对齐,找到具有恒定内存的任意长序列对的对齐。此外,提出了一种启发式的动态重叠算法,使子序列的频带重叠,以提高精度。为了实现ABSW的硬件加速,我们进一步提出了带回溯的带状Smith-Waterman硬件架构。实验表明,ABSW对错误率高达40%的序列产生了接近最优的比对分数。我们的硬件实现的ABSW比软件实现的要高出200倍。
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