Evidence map›Paper›PMID 38100178›Full record

ArticleMicrobial genomics2023

Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on

Timothy J Davies, Jeremy Swann, Anna E Sheppard, Hayleigh Pickford, Samuel Lipworth, Manal AbuOun, Matthew J Ellington, Philip W Fowler, Susan Hopkins, Katie L Hopkins and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microbial genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
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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

15 authors.

Timothy J DaviesNuffield Department of Medicine, Oxford University, Oxford, UK.
Jeremy SwannNuffield Department of Medicine, Oxford University, Oxford, UK.
Anna E SheppardNuffield Department of Medicine, Oxford University, Oxford, UK.
Hayleigh PickfordNuffield Department of Medicine, Oxford University, Oxford, UK.
Samuel LipworthNuffield Department of Medicine, Oxford University, Oxford, UK.
Manal AbuOunBacteriology, Animal and Plant Health Agency, Surrey, UK.
Matthew J EllingtonNational Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford, Oxford, UK.
Philip W FowlerNuffield Department of Medicine, Oxford University, Oxford, UK.
Susan HopkinsNational Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford, Oxford, UK.
Katie L HopkinsNational Institute for Health Research (NIHR) Health Protection Research Unit on Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford, Oxford, UK.
Derrick W CrookNuffield Department of Medicine, Oxford University, Oxford, UK.
Timothy E A PetoNuffield Department of Medicine, Oxford University, Oxford, UK.
Muna F AnjumBacteriology, Animal and Plant Health Agency, Surrey, UK.
A Sarah WalkerNuffield Department of Medicine, Oxford University, Oxford, UK.
Nicole StoesserNuffield Department of Medicine, Oxford University, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several bioinformatics genotyping algorithms are now commonly used to characterize antimicrobial resistance (AMR) gene profiles in whole-genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly

Indexed as

Escherichia coliGenomicsAlgorithmsAllelesComputational Biologyantimicrobial resistance genotypingEscherichia coligenomicsresistance prediction

Identifiers

PMID38100178
PMCPMC10763500

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.