Overview of Virus Metagenomic Classification Methods and Their Biological Applications

Area of Science:

• Virology
• Bioinformatics
• Computational Biology
• Genomics

Background:

• Metagenomics enables comprehensive, unbiased assessment of viral taxonomic composition in clinical samples.
• Complexity of techniques and lack of standardized analysis present barriers to entry for new users in viral metagenomics.
• Numerous computational tools and workflows exist, complicating selection for specific research or diagnostic needs.

Purpose of the Study:

• To evaluate 49 published computational classification workflows for viral metagenomics through a literature review.
• To assess the ease-of-use and validation rigor of existing viral metagenomics workflows.
• To guide virologists in selecting appropriate workflows for medical diagnostics and biodiversity studies.

Main Methods:

• Systematic literature review of 49 published viral metagenomics classification workflows.
• Categorization of workflows into five general steps to describe their methodologies.
• Assessment of ease-of-use, validation experiments, and summarization of performance scores from previous benchmarks.

Main Results:

• Identified and characterized 49 distinct computational workflows for viral metagenomics.
• Assessed the suitability of workflows for specific applications including diagnostics, surveillance, discovery, and biodiversity studies.
• Investigated correlations between workflow methodologies and their performance metrics.

Conclusions:

• Provided insights into the potential suitability of different viral metagenomics workflows for diverse applications.
• Developed decision trees to aid virologists in selecting workflows for medical or biodiversity research.
• Outlined future directions for the advancement of clinical viral metagenomics.