Evidence map›Paper›PMID 30465642›Full record

ArticleMicrobial genomics2019

PANINI: Pangenome Neighbour Identification for Bacterial Populations.

Khalil Abudahab, Joaquín M Prada, Zhirong Yang, Stephen D Bentley, Nicholas J Croucher, Jukka Corander, David M Aanensen

Abstract read
In one paragraph

Article in Microbial genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  8. Article
  9. Review
  10. Article
  11. Diversity of carbapenem-resistantMicrobial genomics · 2022
    Article
  12. Population Genomics ofmSystems · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. 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

7 authors.

Khalil Abudahab1​Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK.
Joaquín M Prada2​School of Veterinary Medicine, University of Surrey, Guildford, UK.
Zhirong Yang3​Department of Mathematics and Statistics, Helsinki Institute of Information Technology, University of Helsinki, FI-00014 Helsinki, Finland.
Stephen D Bentley4​Pathogen Genomics, Wellcome Trust Sanger Institute, Hinxton, UK.
Nicholas J Croucher5​Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Jukka Corander3​Department of Mathematics and Statistics, Helsinki Institute of Information Technology, University of Helsinki, FI-00014 Helsinki, Finland.
David M Aanensen1​Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK.

Funding

Medical Research Council MR/N019296/1Medical Research Council MR/R015600/1Wellcome Trust
6 · The paper itself

Abstract

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce panini (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. panini is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. panini is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini.

Indexed as

SoftwareBacteriaGenome, BacterialGenomicsMetadataPhylogenyUnsupervised Machine Learningmachine learningmicrobial population genomicspangenomeweb application

Identifiers

PMID30465642
PMCPMC6521588

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.