SRST specifications

Information


Unique identifier OMICS_12777
Name SRST
Alternative name Short Read Sequence Typing
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Sequences flanking each locus, Illumina read data
Input format FASTQ
Output data Locus variants, scores and coverage statistics for each locus and readset
Operating system Unix/Linux, Mac OS
Programming languages Python
License BSD 3-clause “New” or “Revised” License
Computer skills Advanced
Version 0.2.0
Stability Stable
Requirements SAMtools, Scipy, Numpy, bowtie
Maintained Yes

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Maintainer


  • person_outline Kathryn Holt <>

SRST articles

SRST citations

 (3)
2018
PMCID: 5839586

[…] bp and with ≥5× average coverage depth were subject to further analysis., mlst of most of the isolates has been reported [9]. several previously undetermined isolates were characterized here using srst2 [22], which employs bowtie2 [23] to call loci directly from illumina reads based on the s. aureus mlst database (http://saureus.mlst.net). spa types of all the isolates were determined […]

2017
PMCID: 5328445

[…] bioproject prjeb14267 at the european nucleotide archive; see table s1 in the supplemental material) were assembled using spades (18). most (19) was used to call multilocus sequence type (mlst) and srst2 (20) was used for antibiotic resistance genes. single nucleotide polymorphisms (snps) were called using bwa (21) and gatk (22) with acapsular s. pneumoniae r6 (nc_003098) used as a reference. […]

2016
PMCID: 5075713

[…] groups were downloaded in august 2015 (http://www.ncbi.nlm.nih.gov/genome/?term=staphylococcus+aureus). synthetic 5x coverage was generated for each using art(35). mlst types were ascertained using srst2(58) and binstrain subtypes were ascertained using the v2 matrix., for this study we obtained raw mwgs sequence data in fastq files for 1,265 samples from the hmp ftp site […]

SRST institution(s)
Department of Microbiology and Immunology, The University of Melbourne, Melbourne, Australia
SRST funding source(s)
This research was supported by a Victorian Life Sciences Computation Initiative (VLSCI) grant #VR0082.

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