Evidence map›Paper›PMID 25737802›Full record

ArticlePLoS currents2015

High-resolution Genomic Surveillance of 2014 Ebolavirus Using Shared Subclonal Variants.

Kevin J Emmett, Albert Lee, Hossein Khiabanian, Raul Rabadan

Abstract read
In one paragraph

Article in PLoS currents, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  12. Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Article
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  18. Genomic Analysis of Viral Outbreaks.Annual review of virology · 2016
    Review
  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.

Kevin J EmmettDepartment of Physics and Department of Systems Biology, Columbia University, New York, New York, USA.
Albert LeeDepartment of Systems Biology and Department of Biomedical Informatics, Columbia University, New York, New York, USA.
Hossein KhiabanianDepartment of Systems Biology and Department of Biomedical Informatics, Columbia University, New York, New York, USA.
Raul RabadanDepartment of Systems Biology and Department of Biomedical Informatics, Columbia University, New York, New York, USA.

Funding

Nation Center: Multi-Scale Study- Cellular Networks(RMI)U54CA121852 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CALIFANO, ANDREA · 2005 to 2015
$37.4M
Training Program in Computational BiologyT32GM082797 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HONIG, BARRY H · 2008 to 2015
$1.4M
NCI NIH HHS U54 CA121852NIGMS NIH HHS T32 GM082797
6 · The paper itself

Abstract

backgroundViral outbreaks, such as the 2014 ebolavirus, can spread rapidly and have complex evolutionary dynamics, including coinfection and bulk transmission of multiple viral populations. Genomic surveillance can be hindered when the spread of the outbreak exceeds the evolutionary rate, in which case consensus approaches will have limited resolution. Deep sequencing of infected patients can identify genomic variants present in intrahost populations at subclonal frequencies (i.e. <50%). Shared subclonal variants (SSVs) can provide additional phylogenetic resolution and inform about disease transmission patterns.

methodsWe use metrics from population genetics to analyze data from the 2014 ebolavirus outbreak in Sierra Leone and identify phylogenetic signal arising from SSVs. We use methods derived from information theory to measure a lower bound on transmission bottleneck size. RESULTS AND

conclusionsWe identify several SSV that shed light on phylogenetic relationships not captured by consensus-based analyses. We find that transmission bottleneck size is larger than one founder population, yet significantly smaller than the intrahost effective population. Our results demonstrate the important role of shared subclonal variants in genomic surveillance.

Indexed as

ebolavirusgenomic surveilanceintrahost variantstransmission bottleneck

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Registered trials

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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.