Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS.
<h4>Motivation</h4>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 suf...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2015-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0122524 |
id |
doaj-641d3d92c75843afad38d74a3bbfea3b |
---|---|
record_format |
Article |
spelling |
doaj-641d3d92c75843afad38d74a3bbfea3b2021-03-04T08:23:49ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01104e012252410.1371/journal.pone.0122524Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS.Sven WarrisFeyruz YalcinKatherine J L JacksonJan Peter Nap<h4>Motivation</h4>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.<h4>Results</h4>With the Parallel SW Alignment Software (PaSWAS) it is possible (a) to have easy access to the computational power of NVIDIA-based general purpose graphics processing units (GPGPUs) to perform high-speed sequence alignments, and (b) retrieve relevant information such as score, number of gaps and mismatches. The software reports multiple hits per alignment. The added value of the new SW implementation is demonstrated with two test cases: (1) tag recovery in next generation sequence data and (2) isotype assignment within an immunoglobulin 454 sequence data set. Both cases show the usability and versatility of the new parallel Smith-Waterman implementation.https://doi.org/10.1371/journal.pone.0122524 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sven Warris Feyruz Yalcin Katherine J L Jackson Jan Peter Nap |
spellingShingle |
Sven Warris Feyruz Yalcin Katherine J L Jackson Jan Peter Nap Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS. PLoS ONE |
author_facet |
Sven Warris Feyruz Yalcin Katherine J L Jackson Jan Peter Nap |
author_sort |
Sven Warris |
title |
Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS. |
title_short |
Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS. |
title_full |
Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS. |
title_fullStr |
Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS. |
title_full_unstemmed |
Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS. |
title_sort |
flexible, fast and accurate sequence alignment profiling on gpgpu with paswas. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2015-01-01 |
description |
<h4>Motivation</h4>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.<h4>Results</h4>With the Parallel SW Alignment Software (PaSWAS) it is possible (a) to have easy access to the computational power of NVIDIA-based general purpose graphics processing units (GPGPUs) to perform high-speed sequence alignments, and (b) retrieve relevant information such as score, number of gaps and mismatches. The software reports multiple hits per alignment. The added value of the new SW implementation is demonstrated with two test cases: (1) tag recovery in next generation sequence data and (2) isotype assignment within an immunoglobulin 454 sequence data set. Both cases show the usability and versatility of the new parallel Smith-Waterman implementation. |
url |
https://doi.org/10.1371/journal.pone.0122524 |
work_keys_str_mv |
AT svenwarris flexiblefastandaccuratesequencealignmentprofilingongpgpuwithpaswas AT feyruzyalcin flexiblefastandaccuratesequencealignmentprofilingongpgpuwithpaswas AT katherinejljackson flexiblefastandaccuratesequencealignmentprofilingongpgpuwithpaswas AT janpeternap flexiblefastandaccuratesequencealignmentprofilingongpgpuwithpaswas |
_version_ |
1714807914753949696 |