To focus on possibly relevant pathogens in general rather than on a single SARS-CoV-2 protein, we also considered an aggregated score\documentclass[12pt]{minimal} 				\usepackage{amsmath} 				\usepackage{wasysym} 				\usepackage{amsfonts} 				\usepackage{amssymb} 				\usepackage{amsbsy} 				\usepackage{mathrsfs} 				\usepackage{upgreek} 				\setlength{\oddsidemargin}{-69pt} 				\begin{document}$$ S_{s,k } : = log_{2} \left[ \left(N_{s,k} / T_{k} \right) / \left( \left(P_{s} + C \right) / \left( {15^{k} + C} \right) \right) \right], $$\end{document}Ss,k:=log2Ns,k/Tk/Ps+C/15k+C, where \documentclass[12pt]{minimal} 				\usepackage{amsmath} 				\usepackage{wasysym} 				\usepackage{amsfonts} 				\usepackage{amssymb} 				\usepackage{amsbsy} 				\usepackage{mathrsfs} 				\usepackage{upgreek} 				\setlength{\oddsidemargin}{-69pt} 				\begin{document}$$N_{s,k}$$\end{document}Ns,k is the total number of k-mer matched epitopes in species s, and \documentclass[12pt]{minimal} 				\usepackage{amsmath} 				\usepackage{wasysym} 				\usepackage{amsfonts} 				\usepackage{amssymb} 				\usepackage{amsbsy} 				\usepackage{mathrsfs} 				\usepackage{upgreek} 				\setlength{\oddsidemargin}{-69pt} 				\begin{document}$$T_{k} : = \mathop \sum \limits_{s} N_{s,k}$$\end{document}Tk:=∑sNs,k is the number of such epitopes across all species. The pathogens were then ranked according to score (the highest score obtaining rank 1, the lowest score rank n, where n is the number of considered species). Then the average rank is computed over the different parameter combinations k = 6,7,8.