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Development of a Subsequence Correlation Coefficient Feature Vector Method for High-Resolution HIV-1 Subtype
Shuyan Han1, Lily He1, Yihang Tang2
1School of Science, Beijing University of Civil Engineering and Architecture, Beijing, China.
What Is Already Known About This Topic?:
Current HIV-1 subtype classification tools often rely on time-consuming alignment, whereas new non-alignment methods typically target single genes. China lacks a model for specifically predicting the non-B subtype strains prevalent domestically.
What Is Added By This Report?:
We developed a fast alignment-free method (SCCFV-RDA) for building multigene models. It achieved over 99.85% accuracy in classifying an international dataset and 99.7% accuracy in classifying Chinese pol gene data and showed superior recall for key circulating recombinant form subtypes.
What Are The Implications For Public Health Practice?:
This tool provides accurate and efficient computational support for the precise molecular surveillance of HIV-1 in China, thereby facilitating the formulation of targeted prevention and control strategies.
