AFS: identification and quantification of species composition by metagenomic sequencing

Publication type:
Journal article
Metadata:
Autoren
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000402130100020&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1093/bioinformatics/btw822
eISSN
1460-2059
Externe Identifier
  • Clarivate Analytics Document Solution ID: EV9UD
  • PubMed Identifier: 28453677
ISSN
1367-4803
Ausgabe der Veröffentlichung
9
Zeitschrift
BIOINFORMATICS
Paginierung
1396 - 1398
Datum der Veröffentlichung
2017
Status
Published
Titel
AFS: identification and quantification of species composition by metagenomic sequencing
Sub types
  • Article
Ausgabe der Zeitschrift
33

Data source: Web of Science (Lite)

Other metadata sources:
Abstract
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Summary</jats:title> <jats:p>DNA-based methods to detect and quantify taxon composition in biological materials are often based on species-specific polymerase chain reaction, limited to detecting species targeted by the assay. Next-generation sequencing overcomes this drawback by untargeted shotgun sequencing of whole metagenomes at affordable cost. Here we present AFS, a software pipeline for quantification of species composition in food. AFS uses metagenomic shotgun sequencing and sequence read counting to infer species proportions. Using Illumina data from a reference sausage comprising four species, we reveal that AFS is independent of the sequencing assay and library preparation protocol. Cost-saving short (50-bp) single-end reads and Nextera® library preparation yield reliable results.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and Implementation</jats:title> <jats:p>Datasets, binaries and usage instructions are available under http://all-food-seq.sourceforge.net. Raw data is available at NCBI’s SRA with accession number PRJNA271645.</jats:p> </jats:sec> <jats:sec> <jats:title>Supplementary information</jats:title> <jats:p>Supplementary data are available at Bioinformatics online.</jats:p> </jats:sec>
Autoren
DOI
10.1093/bioinformatics/btw822
Editoren
  • Bonnie Berger
eISSN
1367-4811
ISSN
1367-4803
Ausgabe der Veröffentlichung
9
Zeitschrift
Bioinformatics
Sprache
en
Online publication date
2017
Paginierung
1396 - 1398
Datum der Veröffentlichung
2017
Status
Published
Herausgeber
Oxford University Press (OUP)
Herausgeber URL
http://dx.doi.org/10.1093/bioinformatics/btw822
Datum der Datenerfassung
2023
Titel
AFS: identification and quantification of species composition by metagenomic sequencing
Ausgabe der Zeitschrift
33

Data source: Crossref

Abstract
<h4>Summary</h4>DNA-based methods to detect and quantify taxon composition in biological materials are often based on species-specific polymerase chain reaction, limited to detecting species targeted by the assay. Next-generation sequencing overcomes this drawback by untargeted shotgun sequencing of whole metagenomes at affordable cost. Here we present AFS, a software pipeline for quantification of species composition in food. AFS uses metagenomic shotgun sequencing and sequence read counting to infer species proportions. Using Illumina data from a reference sausage comprising four species, we reveal that AFS is independent of the sequencing assay and library preparation protocol. Cost-saving short (50-bp) single-end reads and Nextera ® library preparation yield reliable results.<h4>Availability and implementation</h4>Datasets, binaries and usage instructions are available under http://all-food-seq.sourceforge.net. Raw data is available at NCBI's SRA with accession number PRJNA271645.<h4>Contact</h4>hankeln@uni-mainz.de.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.
Addresses
  • Institute of Computer Science, Johannes Gutenberg University Mainz, 55099 Mainz, Germany.
Autoren
DOI
10.1093/bioinformatics/btw822
eISSN
1367-4811
Externe Identifier
  • PubMed Identifier: 28453677
Funding acknowledgements
  • Johannes Gutenberg University Center for Computational Sciences:
  • Ministry of Justice:
Open access
false
ISSN
1367-4803
Ausgabe der Veröffentlichung
9
Zeitschrift
Bioinformatics (Oxford, England)
Schlüsselwörter
  • Sequence Analysis, DNA
  • Food Microbiology
  • Software
  • Metagenomics
  • High-Throughput Nucleotide Sequencing
Sprache
eng
Medium
Print
Paginierung
1396 - 1398
Datum der Veröffentlichung
2017
Status
Published
Datum der Datenerfassung
2017
Titel
AFS: identification and quantification of species composition by metagenomic sequencing.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
33

Data source: Europe PubMed Central

Abstract
SUMMARY: DNA-based methods to detect and quantify taxon composition in biological materials are often based on species-specific polymerase chain reaction, limited to detecting species targeted by the assay. Next-generation sequencing overcomes this drawback by untargeted shotgun sequencing of whole metagenomes at affordable cost. Here we present AFS, a software pipeline for quantification of species composition in food. AFS uses metagenomic shotgun sequencing and sequence read counting to infer species proportions. Using Illumina data from a reference sausage comprising four species, we reveal that AFS is independent of the sequencing assay and library preparation protocol. Cost-saving short (50-bp) single-end reads and Nextera ® library preparation yield reliable results. AVAILABILITY AND IMPLEMENTATION: Datasets, binaries and usage instructions are available under http://all-food-seq.sourceforge.net. Raw data is available at NCBI's SRA with accession number PRJNA271645. CONTACT: hankeln@uni-mainz.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Date of acceptance
2016
Autoren
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/28453677
DOI
10.1093/bioinformatics/btw822
eISSN
1367-4811
Ausgabe der Veröffentlichung
9
Zeitschrift
Bioinformatics
Schlüsselwörter
  • Food Microbiology
  • High-Throughput Nucleotide Sequencing
  • Metagenomics
  • Sequence Analysis, DNA
  • Software
Sprache
eng
Country
England
Paginierung
1396 - 1398
PII
btw822
Datum der Veröffentlichung
2017
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
2018
Titel
AFS: identification and quantification of species composition by metagenomic sequencing.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
33

Data source: PubMed

Autoren
Zeitschrift
Bioinform.
Artikelnummer
9
Paginierung
1396 - 1398
Datum der Veröffentlichung
2017
Titel
AFS: identification and quantification of species composition by metagenomic sequencing.
Ausgabe der Zeitschrift
33

Data source: DBLP

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