April 21, 2020  |  

BGSA: a bit-parallel global sequence alignment toolkit for multi-core and many-core architectures.

Authors: Zhang, Jikai and Lan, Haidong and Chan, Yuandong and Shang, Yuan and Schmidt, Bertil and Liu, Weiguo

Modern bioinformatics tools for analyzing large-scale NGS datasets often need to include fast implementations of core sequence alignment algorithms in order to achieve reasonable execution times. We address this need by presenting the BGSA toolkit for optimized implementations of popular bit-parallel global pairwise alignment algorithms on modern microprocessors.BGSA outperforms Edlib, SeqAn and BitPAl for pairwise edit distance computations and Parasail, SeqAn and BitPAl when using more general scoring schemes for pairwise alignments of a batch of sequence reads on both standard multi-core CPUs and Xeon Phi many-core CPUs. Furthermore, banded edit distance performance of BGSA on a Xeon Phi-7210 outperforms the highly optimized NVBio implementation on a Titan X GPU for the seed verification stage of a read mapper by a factor of 4.4.BGSA is open-source and available at https://github.com/sdu-hpcl/BGSA.Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected]

Journal: Bioinformatics
DOI: 10.1093/bioinformatics/bty930
Year: 2019

Read Publication

Talk with an expert

If you have a question, need to check the status of an order, or are interested in purchasing an instrument, we're here to help.