DySC : software for greedy clustering of 16S rRNA reads

Publication type:
Journal article
Metadata:
Autoren
Sammlungen
  • metadata
ISSN
1460-2059
Ausgabe der Veröffentlichung
16
Zeitschrift
Bioinformatics
Schlüsselwörter
  • 004 Informatik
  • 004 Data processing
Sprache
eng
Paginierung
Seiten: 2182 - 2183
Datum der Veröffentlichung
2012
Herausgeber
Oxford Univ. Press
Herausgeber URL
http://dx.doi.org/10.1093/bioinformatics/bts355
Datum der Datenerfassung
2020
Datum, an dem der Datensatz öffentlich gemacht wurde
2020
Zugang
Public
Titel
DySC : software for greedy clustering of 16S rRNA reads
Ausgabe der Zeitschrift
28

Data source: METADATA.UB

Other metadata sources:
Autoren
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000307501100015&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1093/bioinformatics/bts355
eISSN
1460-2059
Externe Identifier
  • Clarivate Analytics Document Solution ID: 988OT
  • PubMed Identifier: 22730435
ISSN
1367-4803
Ausgabe der Veröffentlichung
16
Zeitschrift
BIOINFORMATICS
Paginierung
2182 - 2183
Datum der Veröffentlichung
2012
Status
Published
Titel
DySC: software for greedy clustering of 16S rRNA reads
Sub types
  • Article
Ausgabe der Zeitschrift
28

Data source: Web of Science (Lite)

Abstract
<jats:title>Abstract</jats:title> <jats:p>Summary: Pyrosequencing technologies are frequently used for sequencing the 16S ribosomal RNA marker gene for profiling microbial communities. Clustering of the produced reads is an important but time-consuming task. We present Dynamic Seed-based Clustering (DySC), a new tool based on the greedy clustering approach that uses a dynamic seeding strategy. Evaluations based on the normalized mutual information (NMI) criterion show that DySC produces higher quality clusters than UCLUST and CD-HIT at a comparable runtime.</jats:p> <jats:p>Availability and implementation: DySC, implemented in C, is available at http://code.google.com/p/dysc/ under GNU GPL license.</jats:p> <jats:p>Contact:  bertil.schmidt@uni-mainz.de</jats:p> <jats:p>Supplementary Information:  Supplementary data are available at Bioinformatics online.</jats:p>
Autoren
DOI
10.1093/bioinformatics/bts355
eISSN
1367-4811
ISSN
1367-4803
Ausgabe der Veröffentlichung
16
Zeitschrift
Bioinformatics
Sprache
en
Online publication date
2012
Paginierung
2182 - 2183
Datum der Veröffentlichung
2012
Status
Published
Herausgeber
Oxford University Press (OUP)
Herausgeber URL
http://dx.doi.org/10.1093/bioinformatics/bts355
Datum der Datenerfassung
2023
Titel
DySC: software for greedy clustering of 16S rRNA reads
Ausgabe der Zeitschrift
28

Data source: Crossref

Abstract
<h4>Unlabelled</h4>Pyrosequencing technologies are frequently used for sequencing the 16S ribosomal RNA marker gene for profiling microbial communities. Clustering of the produced reads is an important but time-consuming task. We present Dynamic Seed-based Clustering (DySC), a new tool based on the greedy clustering approach that uses a dynamic seeding strategy. Evaluations based on the normalized mutual information (NMI) criterion show that DySC produces higher quality clusters than UCLUST and CD-HIT at a comparable runtime.<h4>Availability and implementation</h4>DySC, implemented in C, is available at http://code.google.com/p/dysc/ under GNU GPL license.
Addresses
  • Institut für Informatik, Johannes Gutenberg University Mainz, Mainz 55099, Germany.
Autoren
DOI
10.1093/bioinformatics/bts355
eISSN
1367-4811
Externe Identifier
  • PubMed Identifier: 22730435
Open access
false
ISSN
1367-4803
Ausgabe der Veröffentlichung
16
Zeitschrift
Bioinformatics (Oxford, England)
Schlüsselwörter
  • RNA, Ribosomal, 16S
  • Cluster Analysis
  • Sequence Analysis, RNA
  • Software
  • Metagenome
Sprache
eng
Medium
Print-Electronic
Online publication date
2012
Paginierung
2182 - 2183
Datum der Veröffentlichung
2012
Status
Published
Datum der Datenerfassung
2012
Titel
DySC: software for greedy clustering of 16S rRNA reads.
Sub types
  • Comparative Study
  • Journal Article
Ausgabe der Zeitschrift
28

Data source: Europe PubMed Central

Abstract
UNLABELLED: Pyrosequencing technologies are frequently used for sequencing the 16S ribosomal RNA marker gene for profiling microbial communities. Clustering of the produced reads is an important but time-consuming task. We present Dynamic Seed-based Clustering (DySC), a new tool based on the greedy clustering approach that uses a dynamic seeding strategy. Evaluations based on the normalized mutual information (NMI) criterion show that DySC produces higher quality clusters than UCLUST and CD-HIT at a comparable runtime. AVAILABILITY AND IMPLEMENTATION: DySC, implemented in C, is available at http://code.google.com/p/dysc/ under GNU GPL license.
Autoren
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/22730435
DOI
10.1093/bioinformatics/bts355
eISSN
1367-4811
Ausgabe der Veröffentlichung
16
Zeitschrift
Bioinformatics
Schlüsselwörter
  • Cluster Analysis
  • Metagenome
  • RNA, Ribosomal, 16S
  • Sequence Analysis, RNA
  • Software
Sprache
eng
Country
England
Paginierung
2182 - 2183
PII
bts355
Datum der Veröffentlichung
2012
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
2013
Titel
DySC: software for greedy clustering of 16S rRNA reads.
Sub types
  • Comparative Study
  • Journal Article
Ausgabe der Zeitschrift
28

Data source: PubMed

Autoren
Zeitschrift
Bioinform.
Artikelnummer
16
Paginierung
2182 - 2183
Datum der Veröffentlichung
2012
Titel
DySC: software for greedy clustering of 16S rRNA reads.
Ausgabe der Zeitschrift
28

Data source: DBLP

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