A Data Analytics-Based Study in SARS-CoV-2 Genome Revealed a Commonality in the Infection Pattern

Severe acute respiratory syndrome (SARS) is an infection caused by the virus SARS-CoV-2, initially reported in the Wuhan province of China. Due to the rapid infectious and mutational capability of the virus, the infection spread across world infecting over 600 million people and causing more than six million deaths. Our aim was to examine the differential mutation profile of SARS-CoV-2 isolated from the deceased and alive patients in order to understand the possible clinical correlation. In this study, we retrieved 304,975 genome sequences of SARS-CoV-2 deposited in GISAID as on February 2021 and analyzed the mutational patterns in 2810 genome sequences based on availability of patient specific information covering six countries (India, France, USA, Mexico, Brazil, and Italy). Our analysis of the dataset using data analytics in Python and Tableau revealed large variation in mutations observed in the virus strains isolated from alive and deceased patients in different countries. We observed the D614G mutation in the spike protein and P323L in NSP12 in all six countries. In general, we observed that the mortality rate of male patients was always greater than that of female patients in every age group. Some of the mutations (N203K and N204R) in the nucleocapsid protein of SARS-CoV-2 was common to both alive and deceased patients of Brazil. There was a lack of correlation between mutations specific to alive and deceased patients.