Parallel and scalable short-read alignment on multi-core clusters using UPC++

Publikationstyp:
Zeitschriftenaufsatz
Metadaten:
Autoren
Sammlungen
  • metadata
ISSN
1932-6203
Ausgabe der Veröffentlichung
1
Zeitschrift
PLoS one
Schlüsselwörter
  • 004 Informatik
  • 004 Data processing
Sprache
eng
Paginierung
e0145490
Datum der Veröffentlichung
2016
Herausgeber
PLoS
Herausgeber URL
http://dx.doi.org/10.1371/journal.pone.0145490
Datum der Datenerfassung
2020
Datum, an dem der Datensatz öffentlich gemacht wurde
2020
Zugang
Public
Titel
Parallel and scalable short-read alignment on multi-core clusters using UPC++
Ausgabe der Zeitschrift
11

Datenquelle: METADATA.UB

Andere Metadatenquellen:
Autoren
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000367801400037&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1371/journal.pone.0145490
Externe Identifier
  • Clarivate Analytics Document Solution ID: DA4VZ
  • PubMed Identifier: 26731399
ISSN
1932-6203
Ausgabe der Veröffentlichung
1
Zeitschrift
PLOS ONE
Artikelnummer
ARTN e0145490
Datum der Veröffentlichung
2016
Status
Published
Titel
Parallel and Scalable Short-Read Alignment on Multi-Core Clusters Using UPC plus
Sub types
  • Article
Ausgabe der Zeitschrift
11

Datenquelle: Web of Science (Lite)

Autoren
DOI
10.1371/journal.pone.0145490
Editoren
  • Chongle Pan
eISSN
1932-6203
Ausgabe der Veröffentlichung
1
Zeitschrift
PLOS ONE
Sprache
en
Online publication date
2016
Paginierung
e0145490 - e0145490
Status
Published online
Herausgeber
Public Library of Science (PLoS)
Herausgeber URL
http://dx.doi.org/10.1371/journal.pone.0145490
Datum der Datenerfassung
2019
Titel
Parallel and Scalable Short-Read Alignment on Multi-Core Clusters Using UPC++
Ausgabe der Zeitschrift
11

Datenquelle: Crossref

Abstract
The growth of next-generation sequencing (NGS) datasets poses a challenge to the alignment of reads to reference genomes in terms of alignment quality and execution speed. Some available aligners have been shown to obtain high quality mappings at the expense of long execution times. Finding fast yet accurate software solutions is of high importance to research, since availability and size of NGS datasets continue to increase. In this work we present an efficient parallelization approach for NGS short-read alignment on multi-core clusters. Our approach takes advantage of a distributed shared memory programming model based on the new UPC++ language. Experimental results using the CUSHAW3 aligner show that our implementation based on dynamic scheduling obtains good scalability on multi-core clusters. Through our evaluation, we are able to complete the single-end and paired-end alignments of 246 million reads of length 150 base-pairs in 11.54 and 16.64 minutes, respectively, using 32 nodes with four AMD Opteron 6272 16-core CPUs per node. In contrast, the multi-threaded original tool needs 2.77 and 5.54 hours to perform the same alignments on the 64 cores of one node. The source code of our parallel implementation is publicly available at the CUSHAW3 homepage (http://cushaw3.sourceforge.net).
Addresses
  • Parallel and Distributed Architectures Group, Johannes Gutenberg University Mainz, Mainz, Germany.
Autoren
DOI
10.1371/journal.pone.0145490
eISSN
1932-6203
Externe Identifier
  • PubMed Identifier: 26731399
  • PubMed Central ID: PMC4711716
Open access
true
ISSN
1932-6203
Ausgabe der Veröffentlichung
1
Zeitschrift
PloS one
Schlüsselwörter
  • Humans
  • Reproducibility of Results
  • Sequence Alignment
  • Computational Biology
  • Genome, Human
  • Algorithms
  • Internet
  • Programming Languages
  • High-Throughput Nucleotide Sequencing
Sprache
eng
Medium
Electronic-eCollection
Online publication date
2016
Open access status
Open Access
Paginierung
e0145490
Datum der Veröffentlichung
2016
Status
Published
Publisher licence
CC BY
Datum der Datenerfassung
2016
Titel
Parallel and Scalable Short-Read Alignment on Multi-Core Clusters Using UPC+.
Sub types
  • research-article
  • Journal Article
Ausgabe der Zeitschrift
11

Files

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0145490&type=printable https://europepmc.org/articles/PMC4711716?pdf=render

Datenquelle: Europe PubMed Central

Abstract
The growth of next-generation sequencing (NGS) datasets poses a challenge to the alignment of reads to reference genomes in terms of alignment quality and execution speed. Some available aligners have been shown to obtain high quality mappings at the expense of long execution times. Finding fast yet accurate software solutions is of high importance to research, since availability and size of NGS datasets continue to increase. In this work we present an efficient parallelization approach for NGS short-read alignment on multi-core clusters. Our approach takes advantage of a distributed shared memory programming model based on the new UPC++ language. Experimental results using the CUSHAW3 aligner show that our implementation based on dynamic scheduling obtains good scalability on multi-core clusters. Through our evaluation, we are able to complete the single-end and paired-end alignments of 246 million reads of length 150 base-pairs in 11.54 and 16.64 minutes, respectively, using 32 nodes with four AMD Opteron 6272 16-core CPUs per node. In contrast, the multi-threaded original tool needs 2.77 and 5.54 hours to perform the same alignments on the 64 cores of one node. The source code of our parallel implementation is publicly available at the CUSHAW3 homepage (http://cushaw3.sourceforge.net).
Date of acceptance
2015
Autoren
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/26731399
DOI
10.1371/journal.pone.0145490
eISSN
1932-6203
Externe Identifier
  • PubMed Central ID: PMC4711716
Ausgabe der Veröffentlichung
1
Zeitschrift
PLoS One
Schlüsselwörter
  • Algorithms
  • Computational Biology
  • Genome, Human
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Internet
  • Programming Languages
  • Reproducibility of Results
  • Sequence Alignment
Sprache
eng
Country
United States
Paginierung
e0145490
PII
PONE-D-15-47250
Datum der Veröffentlichung
2016
Status
Published online
Datum, an dem der Datensatz öffentlich gemacht wurde
2016
Titel
Parallel and Scalable Short-Read Alignment on Multi-Core Clusters Using UPC+.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
11

Datenquelle: PubMed

Author's licence
CC-BY
Autoren
Hosting institution
Universitätsbibliothek Mainz
Sammlungen
  • DFG-OA-Publizieren (2012 - 2017)
Resource version
Published version
DOI
10.1371/journal.pone.0145490
Funding acknowledgements
  • DFG, Open Access-Publizieren Universität Mainz / Universitätsmedizin
File(s) embargoed
false
Open access
true
ISSN
1932-6203
Ausgabe der Veröffentlichung
1
Zeitschrift
PLoS one
Schlüsselwörter
  • 004 Informatik
  • 004 Data processing
Sprache
eng
Open access status
Open Access
Paginierung
e0145490
Datum der Veröffentlichung
2016
Public URL
https://openscience.ub.uni-mainz.de/handle/20.500.12030/7432
Herausgeber
PLoS
Herausgeber URL
http://dx.doi.org/10.1371/journal.pone.0145490
Datum der Datenerfassung
2022
Datum, an dem der Datensatz öffentlich gemacht wurde
2022
Zugang
Public
Titel
Parallel and scalable short-read alignment on multi-core clusters using UPC++
Ausgabe der Zeitschrift
11

Files

parallel_and_scalable_shortre-20220712210247913.pdf

Datenquelle: OPENSCIENCE.UB

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