Evidence map›Paper›PMID 27098043›Full record

ArticleNucleic acids research2016

EDGAR 2.0: an enhanced software platform for comparative gene content analyses.

Jochen Blom, Julian Kreis, Sebastian Spänig, Tobias Juhre, Claire Bertelli, Corinna Ernst, Alexander Goesmann

Abstract readComparative Study
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 181 papers.

0numbers the graph read from it
0cells of the map it votes in
181citing 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

181 citing papers in PubMed.

  1. Article
  2. Functional Genome Annotation ofJournal of microbiology and biotechnology · 2026
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  8. Genome-based development and clinical evaluation of a customized LAMP panel to rapidly detect, quantify, and determine antibiotic sensitivity of Escherichia coli in native urine samples from urological patients.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Genotypes and associated traits inFrontiers in microbiology · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Evolution and Competitive Struggles ofInternational journal of molecular sciences · 2024
    Article
  17. Microorganisms · 2024
    Article
  18. Article
  19. Article
  20. Methods for Pangenomic Core Detection.Methods in molecular biology (Clifton, N.J.) · 2024
    Article

121 more citing papers are in PubMed but not listed here.

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

7 authors.

Jochen BlomBioinformatics & Systems Biology, Justus-Liebig-University Giessen, 35392 Giessen, Hesse, Germany jochen.blom@computational.bio.uni-giessen.de.ORCID http://orcid.org/0000-0001-6455-3622
Julian KreisBioinformatics & Systems Biology, Justus-Liebig-University Giessen, 35392 Giessen, Hesse, Germany.
Sebastian SpänigBioinformatics & Systems Biology, Justus-Liebig-University Giessen, 35392 Giessen, Hesse, Germany.
Tobias JuhreBioinformatics & Systems Biology, Justus-Liebig-University Giessen, 35392 Giessen, Hesse, Germany.
Claire BertelliInstitute of Microbiology, University Hospital Center and University of Lausanne, 1011 Lausanne, VD, Switzerland SIB Swiss Institute of Bioinformatics, 1015 Lausanne, VD, Switzerland.
Corinna ErnstCenter for Familial Breast and Ovarian Cancer, Medical Faculty, University Hospital Cologne, University of Cologne, 50931 Cologne, NRW, Germany.
Alexander GoesmannBioinformatics & Systems Biology, Justus-Liebig-University Giessen, 35392 Giessen, Hesse, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapidly increasing availability of microbial genome sequences has led to a growing demand for bioinformatics software tools that support the functional analysis based on the comparison of closely related genomes. By utilizing comparative approaches on gene level it is possible to gain insights into the core genes which represent the set of shared features for a set of organisms under study. Vice versa singleton genes can be identified to elucidate the specific properties of an individual genome. Since initial publication, the EDGAR platform has become one of the most established software tools in the field of comparative genomics. Over the last years, the software has been continuously improved and a large number of new analysis features have been added. For the new version, EDGAR 2.0, the gene orthology estimation approach was newly designed and completely re-implemented. Among other new features, EDGAR 2.0 provides extended phylogenetic analysis features like AAI (Average Amino Acid Identity) and ANI (Average Nucleotide Identity) matrices, genome set size statistics and modernized visualizations like interactive synteny plots or Venn diagrams. Thereby, the software supports a quick and user-friendly survey of evolutionary relationships between microbial genomes and simplifies the process of obtaining new biological insights into their differential gene content. All features are offered to the scientific community via a web-based and therefore platform-independent user interface, which allows easy browsing of precomputed datasets. The web server is accessible at http://edgar.computational.bio.

Indexed as

SoftwareComputational BiologyConserved SequenceDatabases, GeneticDatasets as TopicInternetMicrobial ConsortiaPhylogenySpecies SpecificitySynteny

Identifiers

PMID27098043
PMCPMC4987874

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.