CAFA-evaluator: a Python tool for benchmarking ontological classification methods

Author:

Piovesan Damiano1ORCID,Zago Davide2,Joshi Parnal23ORCID,De Paolis Kaluza M Clara4,Mehdiabadi Mahta1,Ramola Rashika4,Monzon Alexander Miguel5ORCID,Reade Walter6,Friedberg Iddo3ORCID,Radivojac Predrag4ORCID,Tosatto Silvio C E1ORCID

Affiliation:

1. Department of Biomedical Sciences, University of Padova , 35121 Padova, Italy

2. Program in Bioinformatics and Computational Biology, Iowa State University , Ames, IA 50011, United States

3. Department of Veterinary Microbiology and Preventive Medicine, Iowa State University , Ames, IA 50011, United States

4. Khoury College of Computer Sciences, Northeastern University , Boston, MA 02115, United States

5. Department of Information Engineering, University of Padova , 35121 Padova, Italy

6. Kaggle , San Francisco, CA, United States

Abstract

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. Availability and implementation https://pypi.org/project/cafaeval

Funder

COST

European Cooperation in Science and Technology

European Union

National Center for Gene Therapy and Drugs

Italian Ministry of Education and Research

Publisher

Oxford University Press (OUP)

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