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BioinformaticsbioRxiv
Preprint

RASCL: Rapid Assessment Of SARS-CoV-2 Clades Through Molecular Sequence Analysis

Alexander G. LucaciiD, Jordan D. ZehriD, Stephen D. ShankiD, Dave BouvieriD, Mei HaniD, Anton NekrutenkoiD, Darren Patrick MartiniD, Sergei L. Kosakovsky PondiD

Abstract

An important component of efforts to manage the ongoing COVID19 pandemic is the Rapid Assessment of how natural selection contributes to the emergence and proliferation of potentially dangerous SARS-CoV-2 lineages and CLades (RASCL). The RASCL pipeline enables continuous comparative phylogenetics-based selection analyses of rapidly growing clade-focused genome surveillance datasets, such as those produced following the initial detection of potentially dangerous variants. From such datasets RASCL automatically generates down-sampled codon alignments of individual genes/ORFs containing contextualizing background reference sequences, analyzes these with a battery of selection tests, and outputs results as both machine readable JSON files, and interactive notebook-based visualizations. AvailabilityRASCL is available from a dedicated repository at https://github.com/veg/RASCL and as a Galaxy workflow https://usegalaxy.eu/u/hyphy/w/rascl. Existing clade/variant analysis results are available here: https://observablehq.com/@aglucaci/rascl. ContactDr. Sergei L Kosakovsky Pond (spond@temple.edu). Supplementary informationN/A

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02 /Specification & Classification

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