Evidence map›Paper›PMID 29186559›Full record

ArticleMolecular biology and evolution2018

PHYLOSCANNER: Inferring Transmission from Within- and Between-Host Pathogen Genetic Diversity.

Chris Wymant, Matthew Hall, Oliver Ratmann, David Bonsall, Tanya Golubchik, Mariateresa de Cesare, Astrid Gall, Marion Cornelissen, Christophe Fraser, STOP-HCV Consortium, The Maela Pneumococcal Collaboration, and The BEEHIVE Collaboration

Open access · hybridAbstract read
In one paragraph

Article in Molecular biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed
6.8field-weighted citation impact, top 2% of its field
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

101 citing papers in PubMed, 179 citations in OpenAlex.

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  13. Population sequencing for phylogenetic diversity and transmission analyses.Proceedings of the National Academy of Sciences of the United States of America · 2025
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41 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

10 authors at 5 institutions in 2 countries.

Chris WymantBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
Matthew HallBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
Oliver RatmannDepartment of Infectious Disease Epidemiology, Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom.
David BonsallBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
Tanya GolubchikBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
Mariateresa de CesareWellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, United Kingdom.
Astrid GallDepartment of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.
Marion CornelissenLaboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, The Netherlands.
Christophe FraserBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
STOP-HCV Consortium, The Maela Pneumococcal Collaboration, and The BEEHIVE Collaboration
Centre for Human Genetics · GBUniversity of Oxford · GBAmsterdam UMC Location University of Amsterdam · NLImperial College London · GBUniversity of Cambridge · GB

Funding

Medical Research Council MR/K01532X/1Medical Research Council MR/L01632X/1
6 · The paper itself

Abstract

A central feature of pathogen genomics is that different infectious particles (virions and bacterial cells) within an infected individual may be genetically distinct, with patterns of relatedness among infectious particles being the result of both within-host evolution and transmission from one host to the next. Here, we present a new software tool, phyloscanner, which analyses pathogen diversity from multiple infected hosts. phyloscanner provides unprecedented resolution into the transmission process, allowing inference of the direction of transmission from sequence data alone. Multiply infected individuals are also identified, as they harbor subpopulations of infectious particles that are not connected by within-host evolution, except where recombinant types emerge. Low-level contamination is flagged and removed. We illustrate phyloscanner on both viral and bacterial pathogens, namely HIV-1 sequenced on Illumina and Roche 454 platforms, HCV sequenced with the Oxford Nanopore MinION platform, and Streptococcus pneumoniae with sequences from multiple colonies per individual. phyloscanner is available from https://github.com/BDI-pathogens/phyloscanner.

Indexed as

molecular epidemiologymultiple infectionpathogen diversitypathogen genomicspathogen transmissionphylogenetics

Identifiers

PMID29186559
PMCPMC5850600
OpenAlexW2791212039

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.