Precise genotyping and recombination detection of Enterovirus

Area of Science:

• Virology
• Bioinformatics
• Computational Biology

Background:

• Enteroviruses (EV) cause diverse diseases in humans and mammals.
• Accurate EV typing is critical for treatment and disease control.
• Emerging viral strains challenge existing diagnostic tools.

Purpose of the Study:

• To present EVIDENCE, a web-based tool for EV genotyping and recombination detection.
• To improve the sensitivity and specificity of EV identification.
• To aid in clinical diagnosis and understanding EV evolution.

Main Methods:

• Utilizing mixed-ranking scores to evaluate prototype fitness based on relatedness and genomic regions.
• Employing phylogenetic methods for genotype determination via closest neighbor analysis.
• Implementing sliding window analysis to detect recombination events by calculating sequence distance and phylogenetic relationships.

Main Results:

• EVIDENCE provides genotyping and recombination detection pipelines.
• The tool incorporates an updated and comprehensive database of EV reference sequences.
• Interactive visualization of detected recombination events is available.

Conclusions:

• EVIDENCE is the first web tool offering integrated EV genotyping and recombination detection.
• The tool enhances accuracy through updated reference sequences and robust analytical pipelines.
• EVIDENCE accelerates genotype identification, supporting clinical applications and evolutionary studies.