Comparison of functional annotation schemes for genomes

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Functional classification schemes are crucial for organizing and interpreting genomic data.
• Existing schemes vary in scope and architecture, posing challenges for consistent analysis.
• A standardized approach is needed to compare and understand these diverse classification systems.

Purpose of the Study:

• To survey and compare various functional classification schemes for genomes.
• To introduce metrics (depth, breadth, resolution) for characterizing classification schemes.
• To develop a 'Combined Scheme' and graphical representations ('FuncWheels') for visualizing scheme coverage.

Main Methods:

• Comparative analysis of selected functional classification schemes.
• Application of depth, breadth, and resolution metrics.
• Development of a 'Combined Scheme' for mapping existing classifications.
• Generation of 'FuncWheels' for graphical representation of hierarchical schemes.

Main Results:

• Identified significant variations in scope and architecture among current genome functional classification schemes.
• Demonstrated the utility of depth, breadth, and resolution as comparative descriptors.
• 'FuncWheels' effectively illustrated similarities and differences in functional space coverage.
• Highlighted key issues in the design and implementation of gene product functional classifications.

Conclusions:

• The evaluation provides a framework for assessing genome functional classification schemes.
• Graphical representations like 'FuncWheels' aid in understanding classification scheme diversity.
• The findings inform the development of improved, potentially 'second-generation', classification systems.