Evidence map›Paper›PMID 28750049›Full record

ArticlePloS one2017

Genome Target Evaluator (GTEvaluator): A workflow exploiting genome dataset to measure the sensitivity and specificity of genetic markers.

Arnaud Felten, Laurent Guillier, Nicolas Radomski, Michel-Yves Mistou, Renaud Lailler, Sabrina Cadel-Six

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Retrieving Good-QualityBioinformatics and biology insights · 2022
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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

6 authors.

Arnaud FeltenUniversité PARIS-EST, ANSES, Laboratory for Food Safety, Maisons-Alfort, France.
Laurent GuillierUniversité PARIS-EST, ANSES, Laboratory for Food Safety, Maisons-Alfort, France.
Nicolas RadomskiUniversité PARIS-EST, ANSES, Laboratory for Food Safety, Maisons-Alfort, France.
Michel-Yves MistouUniversité PARIS-EST, ANSES, Laboratory for Food Safety, Maisons-Alfort, France.
Renaud LaillerUniversité PARIS-EST, ANSES, Laboratory for Food Safety, Maisons-Alfort, France.
Sabrina Cadel-SixUniversité PARIS-EST, ANSES, Laboratory for Food Safety, Maisons-Alfort, France.ORCID http://orcid.org/0000-0001-5291-2181

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most of the bacterial typing methods used to discriminate isolates in medical or food safety microbiology are based on genetic markers used as targets in PCR or hybridization experiments. These DNA typing methods are important tools for studying prevalence and epidemiology, for conducting surveillance, investigations and control of biological hazard sources. In that perspective, it is crucial to insure that the chosen genetic markers have the greatest specificity and sensitivity. The wealth of whole-genome sequences available for many bacterial species offers the opportunity to evaluate the performance of these genetic markers. In the present study, we have developed GTEvaluator, a bioinformatics workflow which ranks genetic markers depending on their sensitivity and specificity towards groups of well-defined genomes. GTEvaluator identifies the most performant genetic markers to target individuals among a population. The individuals (i.e. a group of genomes within a collection) are defined by any kind of particular phenotypic or biological properties inside a related population (i.e. collection of genomes). The performance of the genetic markers is computed by a distance value which takes into account both sensitivity and specificity. In this study we report two examples of GTEvaluator application. In the first example Bacillus phenotypic markers were evaluated for their capacity to distinguish B. cereus from B. thuringiensis. In the second experiment, GTEvaluator measured the performance of genetic markers dedicated to the molecular serotyping of Salmonella enterica. In one in silico experiment it was possible to test 64 markers onto 134 genomes corresponding to 14 different serotypes.

Indexed as

Databases, GeneticGenome, BacterialBacillus cereusBacillus thuringiensisComputer SimulationGenetic MarkersGenomicsPlasmidsSalmonella entericaSerogroupUncertaintyGenetic Markers

Identifiers

PMID28750049
PMCPMC5531552

What OpenQuestion holds

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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.