Author

Lorenzo Pellis

University of ManchesterORCID 0000-0002-3436-6487Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Organism:virus· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Katrina LythgoeiD· 2 shared Amy TrebesiD· 1 shared Andrew NelsoniD· 1 shared Anel NurtayiD· 1 shared Angela GreeniD· 1 shared Christophe FraseriD· 1 shared Clare M. McCanniD· 1 shared Darren SmithiD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Katrina LythgoeORCID

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2 papers

Recent·Most cited

Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods

Roberto Cahuantzi, Katrina Lythgoe, Ian Hall, Lorenzo Pellis, Thomas House

This paper develops scalable machine learning methods to identify significant SARS-CoV-2 lineages from genomic data, offering a complementary approach to traditional phylogenetic analysis.

Proceedings of the National Academy of Sciences · Mar 13, 2024Peer-reviewedBioinformatics

Viral burdens are associated with age and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection related sampling bias.

Helen R. Fryer, Tanya Golubchik, Matthew D. Hall, Christophe Fraser, Robert Hinch, Luca Ferretti A, Laura Thomson, Anel Nurtay, Lorenzo Pellis, George MacIntyre-Cockett, Amy Trebes, David Buck, Paolo Piazza, Angela Green, Lorne J. Lonie, , Katrina Lythgoe

This study adjusts for sampling bias in SARS-CoV-2 Ct values and finds that viral variant and age affect within-host viral burdens, with variant effects varying by vaccination status.

bioRxiv · Dec 2, 2022 · PreprintGenetics