HIV-1 genetic diversity in sub-Saharan Africa is broad and the AIDS epidemic is driven predominantly by recombinants in Central and West Africa. The classification of HIV-1 strains is therefore necessary to understand diagnostic efficiency, individual treatment responses as well as options for designing vaccines and antiretroviral (ARV) treatment guidelines. More so, accurate subtyping of a partial or full genome would represent the population dynamics of HIV and provide evidence for designing surveillance strategies within a geographic region. Evaluating the performance of rapid subtyping tools with options that incorporate phylogeny could be fast, more user-friendly and of high performance. A total of 570 HIV-1 partial sequences from Cameroon, Angola, Democratic Republic of Congo, Gabon and Senegal were obtained from the Los Alamos National Library (LANL) HIV Sequence Database. Phylogeny was performed using MEGA v6 and the results were used to evaluate the performance of eleven different rapid HIV-1 subtyping tools: REGA v2, REGA v3, NCBI, Stanford HIVDB, SUDI, Geno2Pheno, Euresist, STAR, jpHMM, COMET and SCUEAL. The performance of these subtyping tools differed among HIV-1 clades and across different viral genes. NCBI and SUDI showed the highest performance in subtyping. The discordance observed between the rapid subtyping tools and phylogeny implies that phylogenetic analysis is still the more suitable method for HIV-1 classification. However, the need to update the reference datasets of the subtyping tools, and validate algorithms for rapid subtyping and quality control is imperative as this information is relevant for clinical use and policy-making to the AIDS response.
Key words: HIV, phylogeny, performance, subtyping tools, algorithm.
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