Published February 19, 2024
| Version v1
Journal
Open
Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data
Creators
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Sutcliffe, Steven G
(Data manager)1
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Kraemer, Susanne1
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Ellmen, Isaac2
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Knapp, Jennifer2
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Overton, Alyssa2
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Nash, Delaney2
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Nissimov, Jozef2
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Charles, Trevor2
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Dreifuss, David3, 4
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Topolsky, Ivan3, 4
- Baykal, Pelin3, 4
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Fuhrmann, Lara3, 4
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Jablonski, Kim3, 4
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Beerenwinkel, Niko3, 4
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Levy, Joshua5
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Olabode, Abayomi6
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Becker, Devan6
- Gugan, Gopi6
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Britnell, Erin6
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Poon, Art6
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Valieris, Renan7
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Drummond, Rodrigo7
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Defelicibus, Alexandre7
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Dias-Neto, Emmanuel8
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Rosales, Rafael9
- Tojal da Silva, Israel7
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Orfanou, Aspasia10
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Psomopoulos, Fotis10
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Pechlivanis, Nikolaos10
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Pipes, Lenore11
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Chen, Zihao12
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Baaijens, Jasmijn13, 14
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Baym, Michael14
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Jesse, Shapiro1
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1.
McGill University
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2.
University of Waterloo
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3.
ETH Zurich
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4.
SIB Swiss Institute of Bioinformatics
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5.
Scripps Research Institute
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6.
Western University
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7.
AC Camargo Hospital
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8.
Rutgers, The State University of New Jersey
- 9. Universidade de Sao Paulo
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10.
Centre for Research and Technology Hellas
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11.
University of California, Berkeley
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12.
Peking University
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13.
Delft University of Technology
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14.
Harvard Medical School
Description
Synthetic samples created for the benchmarking of wastewater SARS-CoV-2 variant detection pipelines. Each computational strategy was run using a semi-blind approach by the team.
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