Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS

Sven Warris; Feyruz Yalcin; Katherine J.L.  Jackson; Jan Peter Nap

Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS

Sven Warris, Feyruz Yalcin, Katherine J.L. Jackson, Jan Peter Nap

Life Sciences & Renewable Energy

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis.

Original language	English
Number of pages	13
Journal	PLoS ONE
Publication status	Published - 1 Apr 2015

Keywords

bioinformatics

Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)

Renewable fuels and sustainable gases

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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flexiblefastandaccurateFinal published version, 1.44 MB

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title = "Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS",

abstract = "To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis.",

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AU - Warris, Sven

AU - Yalcin, Feyruz

AU - Jackson, Katherine J.L.

AU - Nap, Jan Peter

PY - 2015/4/1

Y1 - 2015/4/1

N2 - To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis.

AB - To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis.

KW - bioinformatics

KW - bioinformatica

M3 - Article

SN - 1932-6203

JO - PLoS ONE

JF - PLoS ONE

ER -

Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS

Abstract

Keywords

Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)

UN SDGs

Access to Document

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Cite this