Comparing full variation profile analysis with the conventional consensus method in SARS-CoV-2 phylogeny

This study proposes a novel approach to studying SARS-CoV-2 virus mutations through sequencing data comparison. Traditional consensus-based methods, which focus on the most common nucleotide at each position, might overlook or obscure the presence of low-frequency variants. Our method, in contrast, retains all sequenced nucleotides at each position, forming a genomic matrix. Utilizing simulated short reads from genomes with specified mutations, we contrasted our genomic matrix approach with the consensus sequence method. Our matrix methodology accurately reflected the known mutations and true compositions, demonstrating its efficacy in understanding the sample variability and their interconnections. Further tests using real data from GISAID and NCBI-SRA confirmed its reliability and robustness. As we see, the genomic matrix approach offers a more accurate representation of the viral genomic diversity, thereby providing superior insights into virus evolution and epidemiology. Future application recommendations are provided based on our observed results.