Análise de similaridade genômica entre diferentes coronavírus: a contribuição dos métodos K-mer e natural vector

Abstract

Studies involving genomic sequence alignment methods have existed since the 1970s. However, the process of aligning these sequences remains relatively time-consuming and requires more powerful computers, both for analysis with viral genomes and particularly with bacterial genomes. In this regard, alignment-free methods can overcome this issue by achieving the same level of accuracy with significantly reduced analysis time. This thesis conducted studies considering two alignment-free methods, one based on k-mer and the other, Natural Vector, in viral genome classification. The k-mer method maintained precision and achieved a shorter analysis time, accurately segregating the groups corresponding to variants and lineages of SARS-CoV-2 sequences compared to the traditional alignment method. The Natural Vector method accurately classified different species of coronaviruses while also considering less time. As each method demonstrated precision and analysis time was a critical factor, it is evident that both methods complement each other in classifying new viruses: Natural Vector correctly identifies the species of coronavirus under study, while k-mer succinctly groups the viruses within the species. Swift classification of coronavirus sequences is paramount for epidemic control, especially during viral outbreaks, as analysis time is crucial in such scenarios.