GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach
Müller R, Nebel M (2018)
BMC Bioinformatics 19(1): 321.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Einrichtung
Abstract / Bemerkung
**Background**: Massive genomic data sets from high-throughput sequencing allow for new insights into complex biological systems such as microbial communities. Analyses of their diversity and structure are typically preceded by clustering millions of 16S rRNA gene sequences into OTUs. Swarm introduced a new clustering strategy which addresses important conceptual and performance issues of the popular de novo clustering approach. However, some parts of the new strategy, e.g. the fastidious option for increased clustering quality, come with their own restrictions.
**Results:** In this paper, we present the new exact, alignment-based de novo clustering tool GeFaST, which implements a generalisation of Swarm’s fastidious clustering. Our tool extends the fastidious option to arbitrary clustering thresholds and allows to adjust its greediness. GeFaST was evaluated on mock-community and natural data and achieved higher clustering quality and performance for small to medium clustering thresholds compared to Swarm and other de novo tools. Clustering with GeFaST was between 6 and 197 times as fast as with Swarm, while the latter required up to 38% less memory for non-fastidious clustering but at least three times as much memory for fastidious clustering.
**Conclusions:** GeFaST extends the scope of Swarm’s clustering strategy by generalising its fastidious option, thereby allowing for gains in clustering quality, and by increasing its performance (especially in the fastidious case). Our evaluations showed that GeFaST has the potential to leverage the use of the (fastidious) clustering strategy for higher thresholds and on larger data sets.
Stichworte
Sequence clustering;
Operational taxonomic units;
Microbial community analysis
Erscheinungsjahr
2018
Zeitschriftentitel
BMC Bioinformatics
Band
19
Ausgabe
1
Art.-Nr.
321
ISSN
1471-2105
eISSN
1471-2105
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Deutsche Forschungsgemeinschaft und die Universität Bielefeld gefördert.
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https://pub.uni-bielefeld.de/record/2931048
Zitieren
Müller R, Nebel M. GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach. BMC Bioinformatics. 2018;19(1): 321.
Müller, R., & Nebel, M. (2018). GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach. BMC Bioinformatics, 19(1), 321. doi:10.1186/s12859-018-2349-1
Müller, Robert, and Nebel, Markus. 2018. “GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach”. BMC Bioinformatics 19 (1): 321.
Müller, R., and Nebel, M. (2018). GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach. BMC Bioinformatics 19:321.
Müller, R., & Nebel, M., 2018. GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach. BMC Bioinformatics, 19(1): 321.
R. Müller and M. Nebel, “GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach”, BMC Bioinformatics, vol. 19, 2018, : 321.
Müller, R., Nebel, M.: GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach. BMC Bioinformatics. 19, : 321 (2018).
Müller, Robert, and Nebel, Markus. “GeFaST: An improved method for OTU assignment by generalising Swarm’s fastidious clustering approach”. BMC Bioinformatics 19.1 (2018): 321.
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2019-09-06T09:19:01Z
MD5 Prüfsumme
6467f69717a04cf519369e4ae6f1ab7c
Daten bereitgestellt von European Bioinformatics Institute (EBI)
Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
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Evaluation data for "GeFaST: An improved method for OTU assignment by generalising Swarm's fastidious clustering approach"
Müller R, Nebel M (2018)
Bielefeld University.
Müller R, Nebel M (2018)
Bielefeld University.
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