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Quantitative Methods in DemographyStochastic Comparison Between the Original SARS-CoV 2 Genetic Structure and SARS-CoV 2 - P.1 Variant

Quantitative Methods in Demography: Stochastic Comparison Between the Original SARS-CoV 2 Genetic... [This article is intended to explore the behavior of complete genetic sequences of SARS-CoV 2 - P.1 variant, in comparison with the original sequence of SARS-CoV 2, accession number MN908947 (see López and Tasca (4open, 3:13, 2020) and Wu et al. (Nature 579:265–269, 2020)). The sequences are taken in FASTA format, they will be considered as samples of stochastic processes. Based on this interpretation, stochastic tools derived from Partition Markov Models Garc ı́a and González-López (Entropy 19(4):160, 2017) are applied, specifically from the G-model, introduced in Garc ı́a et al. (4open 3:13, 2020) , to obtain the representation of the behavior of each sequence. From these models, it is confirmed that the structure of the P.1 variant of the virus shows similar traits to the original one. Moreover, by means of a BIC-based metric and the G-model, it is possible to determine that the original sequence of SARS-CoV 2 (MN908947) and the set of sequences of SARS-CoV 2 - P.1 variant differ in certain transition probabilities, which allows identifying exactly the state that produces the discrepancy. We also represent this discrepancy graphically.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Quantitative Methods in DemographyStochastic Comparison Between the Original SARS-CoV 2 Genetic Structure and SARS-CoV 2 - P.1 Variant

Part of the The Springer Series on Demographic Methods and Population Analysis Book Series (volume 52)
Editors: Skiadas, Christos H.; Skiadas, Charilaos
García, Jesús E.; González-López, V. A.; Tasca, G. H.
Quantitative Methods in Demography — May 31, 2022
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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
ISBN
978-3-030-93004-2
Pages
63 –75
DOI
10.1007/978-3-030-93005-9_5
Publisher site
See Chapter on Publisher Site

Abstract

[This article is intended to explore the behavior of complete genetic sequences of SARS-CoV 2 - P.1 variant, in comparison with the original sequence of SARS-CoV 2, accession number MN908947 (see López and Tasca (4open, 3:13, 2020) and Wu et al. (Nature 579:265–269, 2020)). The sequences are taken in FASTA format, they will be considered as samples of stochastic processes. Based on this interpretation, stochastic tools derived from Partition Markov Models Garc ı́a and González-López (Entropy 19(4):160, 2017) are applied, specifically from the G-model, introduced in Garc ı́a et al. (4open 3:13, 2020) , to obtain the representation of the behavior of each sequence. From these models, it is confirmed that the structure of the P.1 variant of the virus shows similar traits to the original one. Moreover, by means of a BIC-based metric and the G-model, it is possible to determine that the original sequence of SARS-CoV 2 (MN908947) and the set of sequences of SARS-CoV 2 - P.1 variant differ in certain transition probabilities, which allows identifying exactly the state that produces the discrepancy. We also represent this discrepancy graphically.]

Published: May 31, 2022

Keywords: Partition Markov models; Bayesian information criterion; Metric between processes

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