ArticleMicrobial genomics2018
Comprehensive assessment of the quality of Salmonella whole genome sequence data available in public sequence databases using the Salmonella in silico Typing Resource (SISTR).
Article in Microbial genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Phylodynamic analysis ofMicrobial genomics · 2026Article
- Contamination of fungal genomes of Onygenaceae (Phylum Ascomycota) in public databases: incidence, detection, and impact.BMC genomics · 2025Article
- One Health study of mobile colistin resistance (Microbiology spectrum · 2025Article
- Whole genome sequencing as a reliable alternative forFrontiers in microbiology · 2025Article
- Genomic characterisation of the population structure and antibiotic resistance ofLancet regional health. Americas · 2024Article
- Review
- The advantage of intergenic regions as genomic features for machine-learning-based host attribution ofMicrobial genomics · 2023Article
- Prevalence and whole genome phylogenetic analysis reveal genetic relatedness between antibiotic resistance Salmonella in hatchlings and older chickens from farms in Nigeria.Poultry science · 2023Article
- Genomic Epidemiology and Multilevel Genome Typing of Australian Salmonella enterica Serovar Enteritidis.Microbiology spectrum · 2023Article
- Genetic diversity of Salmonella enterica isolated over 13 years from raw California almonds and from an almond orchard.PloS one · 2023Article
- Phenotypic and genotypic survey of antibiotic resistance inFrontiers in veterinary science · 2023Article
- Large-scale comparative genomics to refine the organization of the globalMicrobial genomics · 2022Article
- EnteroBase: hierarchical clustering of 100 000s of bacterial genomes into species/subspecies and populations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- Molecular Detection of Some Virulence Genes inArchives of Razi Institute · 2022Article
- Genomic Comparison of Eight Closed Genomes of Multidrug-ResistantFrontiers in microbiology · 2022Article
- Genomic Epidemiology of Multidrug-Resistant Nontyphoidal Salmonella in Young Children Hospitalized for Gastroenteritis.Microbiology spectrum · 2021Article
- Elucidation of global and national genomic epidemiology ofMicrobial genomics · 2021Article
- Comparison of Molecular and In SilicoMicroorganisms · 2021Article
- Salmonella nomenclature in the genomic era: a time for change.Scientific reports · 2021Article
- Serotyping, MLST, and Core Genome MLST Analysis ofFrontiers in microbiology · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Public health and food safety institutions around the world are adopting whole genome sequencing (WGS) to replace conventional methods for characterizing Salmonella for use in surveillance and outbreak response. Falling costs and increased throughput of WGS have resulted in an explosion of data, but questions remain as to the reliability and robustness of the data. Due to the critical importance of serovar information to public health, it is essential to have reliable serovar assignments available for all of the Salmonella records. The current study used a systematic assessment and curation of all Salmonella in the sequence read archive (SRA) to assess the state of the data and their utility. A total of 67 758 genomes were assembled de novo and quality-assessed for their assembly metrics as well as species and serovar assignments. A total of 42 400 genomes passed all of the quality criteria but 30.16 % of genomes were deposited without serotype information. These data were used to compare the concordance of reported and predicted serovars for two in silico prediction tools, multi-locus sequence typing (MLST) and the Salmonella in silico Typing Resource (SISTR), which produced predictions that were fully concordant with 87.51 and 91.91 % of the tested isolates, respectively. Concordance of in silico predictions increased when serovar variants were grouped together, 89.25 % for MLST and 94.98 % for SISTR. This study represents the first large-scale validation of serovar information in public genomes and provides a large validated set of genomes, which can be used to benchmark new bioinformatics tools.
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