Frontiers in Medical Science Research, 2020, 2(3); doi: 10.25236/FMSR.2020.020306.
Qiling Geng1, Bomin Wei1, Zhangcheng Ji1, Tianyang Wu2, Zhinan Wang4 and Shenghong Chen3
1 Princeton International School of Mathematics and Science; PRISMS 19 Lambert Dr, Princeton NJ , USA 08540
2 The Harker School – Upper School, 500 Saratoga Ave., San Jose, CA, USA 95129
3 Shanghai American School, 258 Jinfeng Road, Minhang District, Shanghai, China 201107
4 Shenzhen Middle School, Renmin North Road Shenzhong Street No.18, LuoHu District Shenzhen, Guangdong Province, China 518001
Under the strike of a global pandemic, SARS-CoV-2 has caused a serious global health crisis that challenges worldwide reaction to contain the spread of virus. Numerous studies have been done about SARS-CoV-2 mutation; yet, questions about the correlation between mutation with factors as genders and geographical location are not comprehensively and timely studied. Thus, in this research, we aim to explore the association of the frequency of several mutation hotspots and these factors by generating graphs with R language based on the data of 93625 SARS-CoV-2 genomes analyzed through Python script and conducting statistical tests, in which we failed to reject the null hypothesis that there’s no significant association. Our research has offered insights for the way of mutation of SARS-CoV-2 in different regions and genders, contributing to the understanding of the evolution of SARS-CoV-2, which is of vital importance to the development of a vaccine.
SARS-CoV-2, Coronavirus, vaccine
Medical Science Research (2020) Vol. 2 Issue 3: 35-41. https://doi.org/10.25236/FMSR.2020.020306.
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