Evidence map›Paper›PMID 27067409›Full record

ArticleBMC microbiology2016

SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli.

Matthew D Whiteside, Chad R Laing, Akiff Manji, Peter Kruczkiewicz, Eduardo N Taboada, Victor P J Gannon

Abstract read
In one paragraph

Article in BMC microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
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  6. Review
  7. Pan-genome Analyses of the SpeciesFrontiers in microbiology · 2017
    Article
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Matthew D WhitesideNational Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
Chad R LaingNational Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada. chad.laing@canada.ca.
Akiff ManjiNational Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
Peter KruczkiewiczNational Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
Eduardo N TaboadaNational Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
Victor P J GannonNational Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPredictive genomics is the translation of raw genome sequence data into a phenotypic assessment of the organism. For bacterial pathogens, these phenotypes can range from environmental survivability, to the severity of human disease. Significant progress has been made in the development of generic tools for genomic analyses that are broadly applicable to all microorganisms; however, a fundamental missing component is the ability to analyze genomic data in the context of organism-specific phenotypic knowledge, which has been accumulated from decades of research and can provide a meaningful interpretation of genome sequence data.

resultsIn this study, we present SuperPhy, an online predictive genomics platform ( http://lfz.corefacility.ca/superphy/ ) for Escherichia coli. The platform integrates the analytical tools and genome sequence data for all publicly available E. coli genomes and facilitates the upload of new genome sequences from users under public or private settings. SuperPhy provides real-time analyses of thousands of genome sequences with results that are understandable and useful to a wide community, including those in the fields of clinical medicine, epidemiology, ecology, and evolution. SuperPhy includes identification of: 1) virulence and antimicrobial resistance determinants 2) statistical associations between genotypes, biomarkers, geospatial distribution, host, source, and phylogenetic clade; 3) the identification of biomarkers for groups of genomes on the based presence/absence of specific genomic regions and single-nucleotide polymorphisms and 4) in silico Shiga-toxin subtype.

conclusionsSuperPhy is a predictive genomics platform that attempts to provide an essential link between the vast amounts of genome information currently being generated and phenotypic knowledge in an organism-specific context.

Indexed as

Genome, BacterialDatabases, Nucleic AcidDrug Resistance, BacterialEscherichia coliGenomicsPhenotypeSequence Analysis, DNASoftwareVirulence FactorsVirulence FactorsAnti-microbial resistanceBioinformaticsComparative genomicsEpidemiologyPopulation genomicsSoftwareVirulence factors

Identifiers

PMID27067409
PMCPMC4828761

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.