Reads2Type: a web application for rapid microbial taxonomy identification
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Reads2Type : a web application for rapid microbial taxonomy identification. / Saputra, Dhany; Rasmussen, Simon; Larsen, Mette V; Haddad, Nizar; Sperotto, Maria Maddalena; Aarestrup, Frank M; Lund, Ole; Sicheritz-Pontén, Thomas.
I: BMC Bioinformatics, Bind 16, 398, 25.11.2015.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Reads2Type
T2 - a web application for rapid microbial taxonomy identification
AU - Saputra, Dhany
AU - Rasmussen, Simon
AU - Larsen, Mette V
AU - Haddad, Nizar
AU - Sperotto, Maria Maddalena
AU - Aarestrup, Frank M
AU - Lund, Ole
AU - Sicheritz-Pontén, Thomas
PY - 2015/11/25
Y1 - 2015/11/25
N2 - BACKGROUND: Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the entire genome of microbial isolates. Therefore we have developed Reads2Type, a web-based tool for taxonomy identification based on whole bacterial genome sequence data.RESULTS: Raw sequencing data provided by the user are mapped against a set of marker probes that are derived from currently available bacteria complete genomes. Using a dataset of 1003 whole genome sequenced bacteria from various sequencing platforms, Reads2Type was able to identify the species with 99.5 % accuracy and on the minutes time scale.CONCLUSIONS: In comparison with other tools, Reads2Type offers the advantage of not needing to transfer sequencing files, as the entire computational analysis is done on the computer of whom utilizes the web application. This also prevents data privacy issues to arise. The Reads2Type tool is available at https://www.cbs.dtu.dk/~dhany/reads2type.html.
AB - BACKGROUND: Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the entire genome of microbial isolates. Therefore we have developed Reads2Type, a web-based tool for taxonomy identification based on whole bacterial genome sequence data.RESULTS: Raw sequencing data provided by the user are mapped against a set of marker probes that are derived from currently available bacteria complete genomes. Using a dataset of 1003 whole genome sequenced bacteria from various sequencing platforms, Reads2Type was able to identify the species with 99.5 % accuracy and on the minutes time scale.CONCLUSIONS: In comparison with other tools, Reads2Type offers the advantage of not needing to transfer sequencing files, as the entire computational analysis is done on the computer of whom utilizes the web application. This also prevents data privacy issues to arise. The Reads2Type tool is available at https://www.cbs.dtu.dk/~dhany/reads2type.html.
KW - Bacteria/classification
KW - Bacterial Proteins/genetics
KW - Benchmarking
KW - Classification
KW - DNA, Bacterial/genetics
KW - Databases, Genetic
KW - Genome, Bacterial
KW - Internet
KW - Multilocus Sequence Typing
KW - RNA, Ribosomal, 16S/genetics
KW - Software
U2 - 10.1186/s12859-015-0829-0
DO - 10.1186/s12859-015-0829-0
M3 - Journal article
C2 - 26608174
VL - 16
JO - B M C Bioinformatics
JF - B M C Bioinformatics
SN - 1471-2105
M1 - 398
ER -
ID: 214021371