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[Preprint]. 2022 Jan 18:2022.01.15.476448.
doi: 10.1101/2022.01.15.476448.

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

Alexander G Lucaci  1 , Jordan D Zehr  1 , Stephen D Shank  1 , Dave Bouvier  2 , Han Mei  2 , Anton Nekrutenko  2 , Darren P Martin  3 , Sergei L Kosakovsky Pond  1
Affiliations

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

Alexander G Lucaci et al. bioRxiv. .

Update in

Abstract

An important component of efforts to manage the ongoing COVID19 pandemic is the R apid A ssessment of how natural selection contributes to the emergence and proliferation of potentially dangerous S ARS-CoV-2 lineages and CL ades (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.

Availability: RASCL 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 .

Contact: Dr. Sergei L Kosakovsky Pond ( spond@temple.edu ).

Supplementary information: N/A.

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Figures

Figure 1.
Figure 1.
(A) A flowchart diagram of the main analytic engine of RASCL. (B) Examples of the ObservableHQ visualization notebook elements for the main Omicron clade (BA.1).
See this image and copyright information in PMC

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