CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods

TL;DR

CAFA-evaluator is a Python tool that efficiently benchmarks hierarchical ontological classification methods, supporting multi-label evaluation on DAG-structured targets with high accuracy and ease of use.

Contribution

It introduces a generalizable, efficient Python-based evaluation framework for hierarchical and DAG-structured ontologies, used in protein function prediction benchmarking.

Findings

Replicates CAFA benchmarking with high reliability

Supports evaluation on directed acyclic graph targets

Optimized for efficiency using matrix computation and topological sorting

Abstract

We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software.