Title:	APPLICATIONS OF SARS-COV-2 SEQUENCING DATA
Author(s):	Cláudia Oliveira da Silva, Tatiana Donai Lopes and Brígida Mónica Faria
ISBN:	978-989-8704-21-4
Editors:	Yingcai Xiao, Ajith P. Abraham and Jörg Roth
Year:	2020
Edition:	Single
Keywords:	SARS-CoV-2, Pairwise Alignment, Similarity, Biopython
Type:	Short
First Page:	252
Last Page:	256
Language:	English
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Paper Abstract:	Monitoring and understanding pathogen epidemiology and evolution is crucial, especially during an outbreak. COVID-19 pandemic, caused by the newly identified virus SARS-CoV-2, is one of the current major challenges that require the best scientific and technological means. Secondary to sequencing, one of the most basic steps in the study of the many virus strains is sequence alignment. In this work, the focus was on the search and selection of a Biopython algorithm of global pairwise sequence alignment, its implementation and analysis of effectiveness and complexity. To apply this algorithm, which provides the level of similarity between sequences, it was used SARS-CoV-2 genomic sequences of samples collected in 10 countries to analyse its similarity with the reference sequence (NC_045512). There were obtained very high similarities between all sequences and it was observed a decrease of similarity over time in most of the countries included in this study. These results are concordant with recent ones that are publicly shared. In this context, the algorithm performed effectively and its low complexity will not limit its application in a bigger volume of data.
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