6533b852fe1ef96bd12aadc8

RESEARCH PRODUCT

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

Haidong LanWeiguo LiuYuan ShangYuandong ChanBertil SchmidtJikai Zhang

subject

Statistics and Probability0303 health sciencesMulti-core processorXeonComputer sciencebusiness.industry030302 biochemistry & molecular biologySequence alignmentSequence Analysis DNAParallel computingBiochemistryComputer Science Applications03 medical and health sciencesComputational MathematicsTitan (supercomputer)SoftwareComputational Theory and MathematicsEdit distancebusinessSequence AlignmentMolecular BiologyAlgorithmsSoftwareXeon Phi030304 developmental biology

description

Abstract Motivation 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. Results 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. Availability and implementation BGSA is open-source and available at https://github.com/sdu-hpcl/BGSA. Supplementary information Supplementary data are available at Bioinformatics online.

yearjournalcountryeditionlanguage
2018-06-26Bioinformatics
https://doi.org/10.1093/bioinformatics/bty930