Evidence map›Paper›PMID 31143162›Full record

ArticleFrontiers in microbiology2019

Comparative Analysis of Tools and Approaches for Source Tracking

Balamurugan Jagadeesan, Leen Baert, Martin Wiedmann, Renato H Orsi

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Article
  3. Listeriosis.Nature reviews. Disease primers · 2025
    Review
  4. Review
  5. Article
  6. Article
  7. Exploring the occurrence ofFrontiers in microbiology · 2024
    Article
  8. Article
  9. Foods (Basel, Switzerland) · 2023
    Review
  10. Efflux Pumps and Different Genetic Contexts ofInternational journal of molecular sciences · 2023
    Article
  11. Article
  12. Whole-Genome Sequencing-Based Characterization ofApplied and environmental microbiology · 2022
    Article
  13. PervasiveApplied and environmental microbiology · 2022
    Review
  14. Food science & nutrition · 2022
    Review
  15. Article
  16. A Machine Learning Model for Food Source Attribution ofPathogens (Basel, Switzerland) · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

4 authors.

Balamurugan JagadeesanNestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland.
Leen BaertNestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland.
Martin WiedmannDepartment of Food Science, Cornell University, Ithaca, NY, United States.
Renato H OrsiDepartment of Food Science, Cornell University, Ithaca, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As WGS is increasingly used by food industry to characterize pathogen isolates, users are challenged by the variety of analysis approaches available, ranging from methods that require extensive bioinformatics expertise to commercial software packages. This study aimed to assess the impact of analysis pipelines (i.e., different hqSNP pipelines, a cg/wgMLST pipeline) and the reference genome selection on analysis results (i.e., hqSNP and allelic differences as well as tree topologies) and conclusion drawn. For these comparisons, whole genome sequences were obtained for 40

Indexed as

CFSAN pipelinecore genome MLST (cgMLST)high quality single nucleotide polymorphism (hqSNP)Listeria monocytogenes (L. monocytogenes)Lyve-SETsmoked salmonwhole genome MLST (wgMLST)whole genome sequence (WGS)

Identifiers

PMID31143162
PMCPMC6521219

What OpenQuestion holds

Textmetadata
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.