Reads2Type: a web application for rapid microbial taxonomy identification

Dhany Saputra, Simon Rasmussen, Mette V Larsen, Nizar Haddad, Maria Maddalena Sperotto, Frank M Aarestrup, Ole Lund, Thomas Sicheritz-Pontén

4 Citations (Scopus)

Abstract

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 http://www.cbs.dtu.dk/~dhany/reads2type.html.

Original languageEnglish
Article number398
JournalBMC Bioinformatics
Volume16
ISSN1471-2105
DOIs
Publication statusPublished - 25 Nov 2015
Externally publishedYes

Keywords

  • Bacteria/classification
  • Bacterial Proteins/genetics
  • Benchmarking
  • Classification
  • DNA, Bacterial/genetics
  • Databases, Genetic
  • Genome, Bacterial
  • Internet
  • Multilocus Sequence Typing
  • RNA, Ribosomal, 16S/genetics
  • Software

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