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arXiv · 2101.02304

Statistical challenges in the analysis of sequence and structure data for the COVID-19 spike protein

Shiyu He·Samuel W. K. Wong
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Abstract

As the major target of many vaccines and neutralizing antibodies against SARS-CoV-2, the spike (S) protein is observed to mutate over time. In this paper, we present statistical approaches to tackle some challenges associated with the analysis of S-protein data. We build a Bayesian hierarchical model to study the temporal and spatial evolution of S-protein sequences, after grouping the sequences into representative clusters. We then apply sampling methods to investigate possible changes to the S-protein's 3-D structure as a result of commonly observed mutations. While the increasing spread of D614G variants has been noted in other research, our results also show that the co-occurring mutations of D614G together with S477N or A222V may spread even more rapidly, as quantified by our model estimates.

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Shiyu He, Samuel W. K. Wong. 2021-01-06. Statistical challenges in the analysis of sequence and structure data for the COVID-19 spike protein. https://arxiv.org/abs/2101.02304

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