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      SRST2: Rapid genomic surveillance for public health and hospital microbiology labs

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          Abstract

          Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data.

          Source code is available from http://katholt.github.io/srst2/.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13073-014-0090-6) contains supplementary material, which is available to authorized users.

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          Most cited references47

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

              The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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                Author and article information

                Contributors
                minouye@unimelb.edu.au
                harriet.dashnow@unimelb.edu.au
                lesley-ann.raven@unimelb.edu.au
                mark.schultz@unimelb.edu.au
                bjpope@unimelb.edu.au
                ttomita@unimelb.edu.au
                jzobel@unimelb.edu.au
                kholt@unimelb.edu.au
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                20 November 2014
                20 November 2014
                2014
                : 6
                : 11
                : 90
                Affiliations
                [ ]Medical Systems Biology, Department of Pathology, The University of Melbourne, Parkville, Victoria Australia
                [ ]Department of Microbiology and Immunology, The University of Melbourne, Parkville, Victoria Australia
                [ ]Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia
                [ ]Victorian Life Sciences Computation Initiative, The University of Melbourne, 187 Grattan Street Carlton, Melbourne, Victoria Australia
                [ ]Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria Australia
                [ ]Microbiological Diagnostic Unit, The University of Melbourne, Parkville, Victoria Australia
                Article
                90
                10.1186/s13073-014-0090-6
                4237778
                25422674
                b00a4c77-7a8a-4d89-ad0c-c75ce843bb52
                © Inouye et al.; licensee BioMed Central Ltd. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 17 July 2014
                : 16 October 2014
                Categories
                Software
                Custom metadata
                © The Author(s) 2014

                Molecular medicine
                Molecular medicine

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