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Evolution and epidemic spread of SARS-CoV-2 in Brazil DS Candido, IM Claro, JG De Jesus, WM Souza, FRR Moreira, ... Science 369 (6508), 1255-1260, 2020 | 711 | 2020 |
Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK L du Plessis, JT McCrone, AE Zarebski, V Hill, C Ruis, B Gutierrez, ... Science 371 (6530), 708-712, 2021 | 406 | 2021 |
SARS-CoV-2 within-host diversity and transmission KA Lythgoe, M Hall, L Ferretti, M de Cesare, G MacIntyre-Cockett, ... Science 372 (6539), eabg0821, 2021 | 348 | 2021 |
Ultra-deep, long-read nanopore sequencing of mock microbial community standards SM Nicholls, JC Quick, S Tang, NJ Loman Gigascience 8 (5), giz043, 2019 | 270 | 2019 |
Generation and transmission of interlineage recombinants in the SARS-CoV-2 pandemic B Jackson, MF Boni, MJ Bull, A Colleran, RM Colquhoun, AC Darby, ... Cell 184 (20), 5179-5188. e8, 2021 | 241 | 2021 |
Exploring the genetic architecture of inflammatory bowel disease by whole-genome sequencing identifies association at ADCY7 Y Luo, KM de Lange, L Jostins, L Moutsianas, J Randall, NA Kennedy, ... Nature Genetics, 2017 | 214 | 2017 |
An integrated national scale SARS-CoV-2 genomic surveillance network DM Aanensen, K Abudahab, A Adams, S Afifi, MT Alam, A Alderton, ... Elsevier, 0 | 186* | |
CLIMB-COVID: continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance SM Nicholls, R Poplawski, MJ Bull, A Underwood, M Chapman, ... Genome Biology 22 (1), 1-21, 2021 | 78 | 2021 |
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In-field metagenome and 16S rRNA gene amplicon nanopore sequencing robustly characterize glacier microbiota A Edwards, AR Debbonaire, SM Nicholls, SME Rassner, B Sattler, ... bioRxiv, 073965, 2019 | 41 | 2019 |
Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package EJ Griffiths, RE Timme, CI Mendes, AJ Page, NF Alikhan, D Fornika, ... GigaScience 11, 2022 | 29 | 2022 |
On the complexity of haplotyping a microbial community SM Nicholls, W Aubrey, K De Grave, L Schietgat, CJ Creevey, A Clare Bioinformatics 37 (10), 1360-1366, 2021 | 19 | 2021 |
The PHA4GE SARS-CoV-2 contextual data specification for open genomic epidemiology EJ Griffiths, RE Timme, AJ Page, NF Alikhan, D Fornika, F Maguire, ... MDPI AG, 2020 | 15 | 2020 |
Probabilistic recovery of cryptic haplotypes from metagenomic data SM Nicholls, W Aubrey, K De Grave, L Schietgat, CJ Creevey, A Clare bioRxiv, 117838, 2017 | 4 | 2017 |
Goldilocks: a tool for identifying genomic regions that are ‘just right’ SM Nicholls, A Clare, JC Randall Bioinformatics 32 (13), 2047-2049, 2016 | 3 | 2016 |
Advances in the recovery of haplotypes from the metagenome SM Nicholls, W Aubrey, K de Grave, L Schietgat, CJ Creevey, A Clare bioRxiv, 067215, 2016 | 3 | 2016 |
Computational recovery of enzyme haplotypes from a metagenome S Nicholls Aberystwyth University, 2018 | 2 | 2018 |
Computational haplotype recovery and long-read validation identifies novel isoforms of industrially relevant enzymes from natural microbial communities SM Nicholls, W Aubrey, A Edwards, K de Grave, S Huws, L Schietgat, ... bioRxiv, 223404, 2017 | 2 | 2017 |
Defining the analytical and clinical sensitivity of the ARTIC method for the detection of SARS-CoV-2 NF Alikhan, J Quick, AJ Trotter, SC Robson, M Bashton, GL Kay_, ... medRxiv, 2021 | 1 | 2021 |