Abstract

Statistical Analysis of Energy Measures as Biomarkers of SARS-Covid-2 Variants and Receptors

Khawla Ghannoum Al Chawaf

The COVID-19 outbreak has made it evident that the nature and behavior of SARS-CoV-2 require constant research and surveillance, owing to the high mutation rates that lead to variants. This work focuses on the statistical analysis of energy measures as biomarkers of SARS-CoV-2. Thus, three statistical tests are applied to the data: the multiple ANOVA test for equality of means, Bartlett’s test for equality of variances, and Levene’s test for assessing the homogeneity of variances. These tests aim to determine which energy measure can differentiate between SARS-CoV-2 variants, human cell receptors (GRP78 and ACE2), and their combinations.
To further investigate the specific pairwise differences between groups, Tukey’s HSD test was performed after the ANOVA. The Tukey test provided adjusted p-values (p-adj) for each pairwise comparison, allowing for a more detailed understanding of significant differences in energy measures across variants, receptors, and their combinations.
The proposed approach combines energy measures and sequence data to develop classification systems and brings out the variety of the virus’ genetics and interaction mechanisms. This work aims to improve the accuracy of variant identification and contribute to creating tailored interventions, which would help address the COVID-19 issue and contribute considerably to the global fight against the pandemic.

Keywords: SARS-CoV-2, COVID-19, statistical analysis, variant identification, human receptors, genetic sequences, ANOVA test, Bartlett’s test, Levene’s Test, Tukey’s HSD test.