SARS-CoV-2 lineage assignments using phylogenetic placement/UShER are superior to pangoLEARN machine-learning method.

Publication Year: 2024

DOI:
10.1093/ve/vead085

PMCID:
PMC10868549

PMID:
38361813

Journal Information

Full Title: Virus Evol

Abbreviation: Virus Evol

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Virology

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
5/6
83.3% Transparent
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Evidence found in paper:

"the multiple sequence alignment was performed using multiple alignment using fast fourier transform (mafft) v7 486 ( ) with options--anysymbol--keeplength--6merpair--addfragments on sequences from the local dataset that had less than 10 per cent unknown positions ( n ) as well as lineage consensus reference sequences (available at https://github com/corneliusroemer/pango-sequences ) for a total of 62719 genome sequences.; sequence data with less than 90 per cent genome coverage that were not found in public databases were made available in a public github repository.; the list of the accessions along with metadata and genomic sequences of the global and local datasets used in this study are available on github at https://github com/nychealth/covid-consensus-genomes-pangolin-analysis ."

Evidence found in paper:

"the multiple sequence alignment was performed using multiple alignment using fast fourier transform (mafft) v7 486 ( ) with options--anysymbol--keeplength--6merpair--addfragments on sequences from the local dataset that had less than 10 per cent unknown positions ( n ) as well as lineage consensus reference sequences (available at https://github com/corneliusroemer/pango-sequences ) for a total of 62719 genome sequences.; sequence data with less than 90 per cent genome coverage that were not found in public databases were made available in a public github repository.; the list of the accessions along with metadata and genomic sequences of the global and local datasets used in this study are available on github at https://github com/nychealth/covid-consensus-genomes-pangolin-analysis ."

Evidence found in paper:

"Conflict of interest: None declared."

Evidence found in paper:

"Funding A.d.B.S. acknowledges support from the California Department of Public Health (Contract No. 20-11088). The findings and conclusions in this article are those of the authors and do not necessarily represent the views or opinions of the California Department of Public Health or the California Health and Human Services Agency. COVID sequencing in NYC was supported (in part) by the Epidemiology and Laboratory Capacity (ELC) for Infectious Diseases Cooperative Agreement (Grant Number: ELC DETECT (6NU50CK000517-01-07) funded by the Centers for Disease Control and Prevention (CDC). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC or the Department of Health and Human Services."

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Open Access
Paper is freely available to read
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Last Updated: Aug 05, 2025