Phylogenetic Analysis of SARS-CoV-2 Data Is Difficult Article Swipe
Benoît Morel
,
Pierre Barbera
,
Lucas Czech
,
Ben Bettisworth
,
Lukáš Hübner
,
Sarah Lutteropp
,
Dora Serdari
,
Evangelia Georgia Kostaki
,
Ioannis Mamais
,
Alexey M. Kozlov
,
Pavlos Pavlidis
,
Dimitrios Paraskevis
,
Alexandros Stamatakis
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/molbev/msaa314
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/molbev/msaa314
Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising a quality-filtered subset of 8,736 out of all 16,453 virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be credible. Finally, an automatic classification of the current sequences into subclasses using the mPTP tool for molecular species delimitation is also, as might be expected, not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/molbev/msaa314
- https://academic.oup.com/mbe/article-pdf/38/5/1777/40470410/msaa314.pdf
- OA Status
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- Cited By
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- References
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3110696950Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/molbev/msaa314Digital Object Identifier
- Title
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Phylogenetic Analysis of SARS-CoV-2 Data Is DifficultWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-12-03Full publication date if available
- Authors
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Benoît Morel, Pierre Barbera, Lucas Czech, Ben Bettisworth, Lukáš Hübner, Sarah Lutteropp, Dora Serdari, Evangelia Georgia Kostaki, Ioannis Mamais, Alexey M. Kozlov, Pavlos Pavlidis, Dimitrios Paraskevis, Alexandros StamatakisList of authors in order
- Landing page
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https://doi.org/10.1093/molbev/msaa314Publisher landing page
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https://academic.oup.com/mbe/article-pdf/38/5/1777/40470410/msaa314.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://academic.oup.com/mbe/article-pdf/38/5/1777/40470410/msaa314.pdfDirect OA link when available
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Phylogenetics, Biology, Phylogenetic tree, Evolutionary biology, Inference, Genetics, Artificial intelligence, Computer science, GeneTop concepts (fields/topics) attached by OpenAlex
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173Total citation count in OpenAlex
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2025: 17, 2024: 20, 2023: 27, 2022: 43, 2021: 54Per-year citation counts (last 5 years)
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50Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.considered | 204 |
| abstract_inverted_index.downstream | 196 |
| abstract_inverted_index.mutations. | 86 |
| abstract_inverted_index.particular | 181 |
| abstract_inverted_index.subclasses | 132 |
| abstract_inverted_index.application | 161 |
| abstract_inverted_index.conjunction | 80 |
| abstract_inverted_index.disentangle | 166 |
| abstract_inverted_index.gisaid.org. | 57 |
| abstract_inverted_index.interpreted | 206 |
| abstract_inverted_index.phylogenies | 32 |
| abstract_inverted_index.delimitation | 140 |
| abstract_inverted_index.difficulties | 28 |
| abstract_inverted_index.phylogenetic | 163, 178, 190 |
| abstract_inverted_index.phylogenies, | 201 |
| abstract_inverted_index.computational | 111 |
| abstract_inverted_index.classification | 126 |
| abstract_inverted_index.nextstrain.org. | 23 |
| abstract_inverted_index.quality-filtered | 41 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5025640090 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I102335020, https://openalex.org/I71030271 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.99216095 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |