SHREC: a short-read error correction method
- Publication type:
- Journal article
- Metadata:
-
- Autoren
- Jan Schroeder
- Heiko Schroeder
- Simon J Puglisi
- Ranjan Sinha
- Bertil Schmidt
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000269196000002&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.1093/bioinformatics/btp379
- eISSN
- 1460-2059
- Externe Identifier
- Clarivate Analytics Document Solution ID: 486KX
- PubMed Identifier: 19542152
- ISSN
- 1367-4803
- Ausgabe der Veröffentlichung
- 17
- Zeitschrift
- BIOINFORMATICS
- Paginierung
- 2157 - 2163
- Datum der Veröffentlichung
- 2009
- Status
- Published
- Titel
- SHREC: a short-read error correction method
- Sub types
- Article
- Ausgabe der Zeitschrift
- 25
Data source: Web of Science (Lite)
- Other metadata sources:
-
- Abstract
- <jats:title>Abstract</jats:title> <jats:p>Motivation: Second-generation sequencing technologies produce a massive amount of short reads in a single experiment. However, sequencing errors can cause major problems when using this approach for de novo sequencing applications. Moreover, existing error correction methods have been designed and optimized for shotgun sequencing. Therefore, there is an urgent need for the design of fast and accurate computational methods and tools for error correction of large amounts of short read data.</jats:p> <jats:p>Results: We present SHREC, a new algorithm for correcting errors in short-read data that uses a generalized suffix trie on the read data as the underlying data structure. Our results show that the method can identify erroneous reads with sensitivity and specificity of over 99% and 96% for simulated data with error rates of up to 3% as well as for real data. Furthermore, it achieves an error correction accuracy of over 80% for simulated data and over 88% for real data. These results are clearly superior to previously published approaches. SHREC is available as an efficient open-source Java implementation that allows processing of 10 million of short reads on a standard workstation.</jats:p> <jats:p>Availability: SHREC source code in JAVA is freely available at http://www.informatik.uni-kiel.de/∼jasc/Shrec/</jats:p> <jats:p>Contact: jasc@informatik.uni-kiel.de</jats:p>
- Autoren
- Jan Schröder
- Heiko Schröder
- Simon J Puglisi
- Ranjan Sinha
- Bertil Schmidt
- DOI
- 10.1093/bioinformatics/btp379
- eISSN
- 1367-4811
- ISSN
- 1367-4803
- Ausgabe der Veröffentlichung
- 17
- Zeitschrift
- Bioinformatics
- Sprache
- en
- Online publication date
- 2009
- Paginierung
- 2157 - 2163
- Datum der Veröffentlichung
- 2009
- Status
- Published
- Herausgeber
- Oxford University Press (OUP)
- Herausgeber URL
- http://dx.doi.org/10.1093/bioinformatics/btp379
- Datum der Datenerfassung
- 2023
- Titel
- SHREC: a short-read error correction method
- Ausgabe der Zeitschrift
- 25
Data source: Crossref
- Abstract
- <h4>Motivation</h4>Second-generation sequencing technologies produce a massive amount of short reads in a single experiment. However, sequencing errors can cause major problems when using this approach for de novo sequencing applications. Moreover, existing error correction methods have been designed and optimized for shotgun sequencing. Therefore, there is an urgent need for the design of fast and accurate computational methods and tools for error correction of large amounts of short read data.<h4>Results</h4>We present SHREC, a new algorithm for correcting errors in short-read data that uses a generalized suffix trie on the read data as the underlying data structure. Our results show that the method can identify erroneous reads with sensitivity and specificity of over 99% and 96% for simulated data with error rates of up to 3% as well as for real data. Furthermore, it achieves an error correction accuracy of over 80% for simulated data and over 88% for real data. These results are clearly superior to previously published approaches. SHREC is available as an efficient open-source Java implementation that allows processing of 10 million of short reads on a standard workstation.
- Addresses
- Institut für Informatik, Christian-Albrecht-Universität Kiel, Herman-Rodewald-Strasse 3, 24118 Kiel, Germany. jasc@informatik.uni-kiel.de
- Autoren
- Jan Schröder
- Heiko Schröder
- Simon J Puglisi
- Ranjan Sinha
- Bertil Schmidt
- DOI
- 10.1093/bioinformatics/btp379
- eISSN
- 1367-4811
- Externe Identifier
- PubMed Identifier: 19542152
- Open access
- false
- ISSN
- 1367-4803
- Ausgabe der Veröffentlichung
- 17
- Zeitschrift
- Bioinformatics (Oxford, England)
- Schlüsselwörter
- DNA
- Sequence Analysis, DNA
- Computational Biology
- Genome
- Algorithms
- Research Design
- Time Factors
- Databases, Nucleic Acid
- Sprache
- eng
- Medium
- Print-Electronic
- Online publication date
- 2009
- Paginierung
- 2157 - 2163
- Datum der Veröffentlichung
- 2009
- Status
- Published
- Datum der Datenerfassung
- 2009
- Titel
- SHREC: a short-read error correction method.
- Sub types
- Research Support, Non-U.S. Gov't
- Journal Article
- Ausgabe der Zeitschrift
- 25
Data source: Europe PubMed Central
- Abstract
- MOTIVATION: Second-generation sequencing technologies produce a massive amount of short reads in a single experiment. However, sequencing errors can cause major problems when using this approach for de novo sequencing applications. Moreover, existing error correction methods have been designed and optimized for shotgun sequencing. Therefore, there is an urgent need for the design of fast and accurate computational methods and tools for error correction of large amounts of short read data. RESULTS: We present SHREC, a new algorithm for correcting errors in short-read data that uses a generalized suffix trie on the read data as the underlying data structure. Our results show that the method can identify erroneous reads with sensitivity and specificity of over 99% and 96% for simulated data with error rates of up to 3% as well as for real data. Furthermore, it achieves an error correction accuracy of over 80% for simulated data and over 88% for real data. These results are clearly superior to previously published approaches. SHREC is available as an efficient open-source Java implementation that allows processing of 10 million of short reads on a standard workstation.
- Autoren
- Jan Schröder
- Heiko Schröder
- Simon J Puglisi
- Ranjan Sinha
- Bertil Schmidt
- Autoren-URL
- https://www.ncbi.nlm.nih.gov/pubmed/19542152
- DOI
- 10.1093/bioinformatics/btp379
- eISSN
- 1367-4811
- Ausgabe der Veröffentlichung
- 17
- Zeitschrift
- Bioinformatics
- Schlüsselwörter
- Algorithms
- Computational Biology
- DNA
- Databases, Nucleic Acid
- Genome
- Research Design
- Sequence Analysis, DNA
- Time Factors
- Sprache
- eng
- Country
- England
- Paginierung
- 2157 - 2163
- PII
- btp379
- Datum der Veröffentlichung
- 2009
- Status
- Published
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2009
- Titel
- SHREC: a short-read error correction method.
- Sub types
- Journal Article
- Research Support, Non-U.S. Gov't
- Ausgabe der Zeitschrift
- 25
Data source: PubMed
- Autoren
- Jan Schröder
- Heiko Schröder
- Simon J Puglisi
- Ranjan Sinha
- Bertil Schmidt
- Zeitschrift
- Bioinform.
- Artikelnummer
- 17
- Paginierung
- 2157 - 2163
- Datum der Veröffentlichung
- 2009
- Titel
- SHREC: a short-read error correction method.
- Ausgabe der Zeitschrift
- 25
Data source: DBLP
- Beziehungen:
- Property of