ArticlePloS one2022
A curated dataset of peste des petits ruminants virus sequences for molecular epidemiological analyses.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Epidemiology of Peste des Petits Ruminants in Nigeria: A Review.Frontiers in veterinary science · 2022Pooled it
- Global evolutionary dynamics of peste des petits ruminants virus reveals geographic lineage structuring and clade-defining mutational signatures.Frontiers in microbiology · 2026Article
- Epidemiological and Operational Constraints on the Feasibility of Peste des Petits Ruminants Eradication Target by 2030: Necessity for a New Pragmatic Road Map.Transboundary and emerging diseases · 2026Review
- Comparative evolutionary analyses of peste des petits ruminants virus genetic lineages.Virus evolution · 2024Article
- Complete genome of a 2014 isolate of peste des petits ruminants virus from Ethiopia.Microbiology resource announcements · 2023Article
- A Clinical, Pathological, Epidemiological and Molecular Investigation of Recent Outbreaks of Peste des Petits Ruminants Virus in Domestic and Wild Small Ruminants in the Abu Dhabi Emirate, United Arab Emirates.Veterinary sciences · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Peste des petits ruminants (PPR) is a highly contagious and devastating viral disease infecting predominantly sheep and goats. Tracking outbreaks of disease and analysing the movement of the virus often involves sequencing part or all of the genome and comparing the sequence obtained with sequences from other outbreaks, obtained from the public databases. However, there are a very large number (>1800) of PPRV sequences in the databases, a large majority of them relatively short, and not always well-documented. There is also a strong bias in the composition of the dataset, with countries with good sequencing capabilities (e.g. China, India, Turkey) being overrepresented, and most sequences coming from isolates in the last 20 years. In order to facilitate future analyses, we have prepared sets of PPRV sequences, sets which have been filtered for sequencing errors and unnecessary duplicates, and for which date and location information has been obtained, either from the database entry or from other published sources. These sequence datasets are freely available for download, and include smaller datasets which maximise phylogenetic information from the minimum number of sequences, and which will be useful for simple lineage identification. Their utility is illustrated by uploading the data to the MicroReact platform to allow simultaneous viewing of lineage date and geographic information on all the viruses for which we have information. While preparing these datasets, we identified a significant number of public database entries which contain clear errors, and propose guidelines on checking new sequences and completing metadata before submission.
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