Evidence map›Paper›PMID 38883783›Full record

ArticlemedRxiv : the preprint server for health sciences2024

spread.gl: visualising pathogen dispersal in a high-performance browser application.

Yimin Li, Nena Bollen, Samuel L Hong, Marius Brusselmans, Fabiana Gámbaro, Marc A Suchard, Andrew Rambaut, Philippe Lemey, Simon Dellicour, Guy Baele

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yimin LiDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0009-0007-9939-8192
Nena BollenDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0000-0002-0532-0658
Samuel L HongDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0000-0001-6354-4943
Marius BrusselmansDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0009-0000-2134-1515
Fabiana GámbaroSpatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium.ORCID 0000-0001-7760-2112
Marc A SuchardDepartment of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.ORCID 0000-0001-9818-479X
Andrew RambautInstitute for Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh, EH9 3FL, UK.ORCID 0000-0003-4337-3707
Philippe LemeyDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0000-0003-2826-5353
Simon DellicourDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0000-0001-9558-1052
Guy BaeleDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.ORCID 0000-0002-1915-7732

Funding

Statistical Innovation to Integrate Sequences and Phenotypes for Scalable Phylodynamic InferenceR01AI153044 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Marc A. Suchard · 2021 to 2026
$2.4M
NIAID NIH HHS R01 AI153044Wellcome Trust
6 · The paper itself

Abstract

Phylogeographic analyses are able to exploit the location data associated with sampled molecular sequences to reconstruct the spatio-temporal dispersal history of a pathogen. Visualisation software is commonly used to facilitate the interpretation of the accompanying estimation results, as these are not always easily interpretable. spread.gl is a powerful, open-source and feature-rich browser application that enables smooth, intuitive and user-friendly visualisation of both discrete and continuous phylogeographic inference results, enabling the animation of pathogen geographic dispersal through time. spread.gl can render and combine the visualisation of several data layers, including a geographic layer (e.g., a world map), multiple layers that contain information extracted from the input phylogeny, and different types of layers that represent environmental data. As such, users can explore which environmental data may have shaped pathogen dispersal patterns, that can subsequently be formally tested through more principled statistical analyses. We showcase the visualisation features of spread.gl on several representative pathogen dispersal examples, including the smooth animation of a phylogeny encompassing over 17,000 genomic sequences resulting from a large-scale SARS-CoV-2 analysis.

Indexed as

data visualisationenvironmental factorsgeospatial diffusionphylodynamicsphylogeography

Identifiers

PMID38883783
PMCPMC11177906

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.