About: Reconstructing disease outbreaks from genetic data: a graph approach

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Reconstructing disease outbreaks from genetic data: a graph approach
Creator	Jombart, T Balloux, F Dodd, P Eggo, R
Source	PMC
abstract	Epidemiology and public health planning will increasingly rely on the analysis of genetic sequence data. In particular, genetic data coupled with dates and locations of sampled isolates can be used to reconstruct the spatiotemporal dynamics of pathogens during outbreaks. Thus far, phylogenetic methods have been used to tackle this issue. Although these approaches have proved useful for informing on the spread of pathogens, they do not aim at directly reconstructing the underlying transmission tree. Instead, phylogenetic models infer most recent common ancestors between pairs of isolates, which can be inadequate for densely sampled recent outbreaks, where the sample includes ancestral and descendent isolates. In this paper, we introduce a novel method based on a graph approach to reconstruct transmission trees directly from genetic data. Using simulated data, we show that our approach can efficiently reconstruct genealogies of isolates in situations where classical phylogenetic approaches fail to do so. We then illustrate our method by analyzing data from the early stages of the swine-origin A/H1N1 influenza pandemic. Using 433 isolates sequenced at both the hemagglutinin and neuraminidase genes, we reconstruct the likely history of the worldwide spread of this new influenza strain. The presented methodology opens new perspectives for the analysis of genetic data in the context of disease outbreaks.
has issue date	2010-06-16(xsd:dateTime)
bibo:doi	10.1038/hdy.2010.78
bibo:pmid	20551981
has license	no-cc
sha1sum (hex)	4c9c0f9d91cb34e576d94d77525259cca0aaafa3
schema:url	https://doi.org/10.1038/hdy.2010.78
resource representing a document's title	Reconstructing disease outbreaks from genetic data: a graph approach
has PubMed Central identifier	PMC3183872
has PubMed identifier	20551981
schema:publication	Heredity
resource representing a document's body	covid:4c9c0f9d91cb34e576d94d77525259cca0aaafa3#body_text
is schema:about of	named entity 'data' named entity 'hemagglutinin' named entity 'genetic sequence' named entity 'presented' named entity 'opens' named entity 'INFLUENZA PANDEMIC' named entity 'TRANSMISSION TREE' named entity 'METHODOLOGY' named entity 'EARLY STAGES' named entity 'DIRECTLY' named entity 'UNDERLYING' named entity 'OUTBREAKS' named entity 'GENEALOGIES' named entity 'MODELS' named entity 'HAVE' named entity 'TRANSMISSION' named entity 'APPROACH' named entity 'GRAPH' named entity 'TREES' named entity 'ISSUE' named entity 'PRESENTED' named entity 'phylogenetic' named entity 'introduce' named entity 'reconstruct' named entity 'Epidemiology' named entity 'sampled' named entity 'strain' named entity 'graph' named entity 'data' named entity 'pathogens' named entity 'phylogenetic' named entity 'phylogenetic' named entity 'genetic data' named entity 'public health' named entity 'genealogies' named entity 'Mexico' named entity 'recombination' named entity 'haplotypes' named entity 'algorithm' named entity 'data sets' named entity 'Individual-based' named entity 'disease outbreaks' named entity 'pathogen' named entity 'infectious disease epidemiology' named entity 'diffusion' named entity 'algorithm' named entity 'ClustalW' named entity 'influenza A/H1N1' named entity 'homologous sequences' named entity 'nosocomial' named entity 'weight function' named entity 'phylogenetic reconstructions' named entity 'phylogenetic' named entity 'R software' named entity 'common ancestors' named entity 'viruses' named entity 'phylogenies' named entity 'China' named entity '2009 A/H1N1' named entity 'genealogy' named entity 'sequence evolution' named entity 'influenza' named entity 'H1N1 influenza virus' named entity 'GenBank' named entity 'spatial grid' named entity 'United States' named entity 'infectious disease' named entity 'North America' named entity 'disease outbreaks' named entity 'influenza' named entity 'molecular clock' named entity 'substitution rates' named entity 'genomes' named entity 'infectious disease' named entity 'haplotype' named entity 'Americas' named entity 'algorithm' named entity 'cell cultures'

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