The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations

Abstract

The Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientifi c study and which are typically used to support assertions made by researchers. ECO describes multiple evidence types, including evidence resulting from experimental (i.e., wet lab) techniques, evidence arising from computational methods, statements made by authors (whether or not supported by evidence), and inferences drawn by researchers curating the literature. In addition to summarizing the evidence that supports a particular assertion, ECO also offers a means to document whether a computer or a human performed the process of making the annotation. Incorporating ECO into an annotation system makes it possible to leverage the structure of the ontology such that associated data can be grouped hierarchically, users can select data associated with particular evidence types, and quality control pipelines can be optimized. Today, over 30 resources, including the Gene Ontology, use the Evidence and Conclusion Ontology to represent both evidence and how annotations are made.

DDIEM: Drug Database for Inborn Errors of Metabolism

“…In 113 cases we could not identify a phenotype class matching the described phenotype in these two ontologies and recorded the phenotype as free text; additionally, we requested extension of the HPO with the missing phenotypes so that we can formally include them in DDIEM once they become available in the HPO. In DDIEM, we distinguish between six different types of evidence provided for the affect of a therapeutic procedure on disease-associated phenotypes, and we use the Evidence and Conclusion Ontology [47] to record evidence for our assertions. We distinguish evidence based on animal models (ECO:0000179), clinical trials ECO:0007121), and experiments on cell lines (ECO:0001565).…”

“…In DDIEM, we rely on ontologies in the OBO Foundry [58] as collaboratively developed reference ontologies in the biomedical domain. We represent phenotypes using either the Human Phenotype Ontology (HPO) [45] or the Mammalian Phenotype Ontology (MPO) [46], and we use the Evidence and Conclusion Ontology (ECO) [59] to specify different study types and evidences.…”

A logical model of homology for comparative biology

“…As described above, whether the first 'finger' of birds is homologous or not to that in dinosaurs is a well known example of conflicting evidence. Although we relate homology assertions herein to the data that support them by annotation with homology evidence codes [2] from the Evidence & Conclusion Ontology (ECO) [73,74], they are not implemented in Phenoscape for customized homology reasoning. It may be desirable in the future, however, to allow user selection of homology assertions based on these codes.…”

Using ZFIN: Data Types, Organization, and Retrieval

“…2F), including both those added by ZFIN curators and collaborating organizations, and those determined computationally based on protein sequence, gene family functions, or assignment of keywords at UniProt [12, 13]. The GO annotation uses evidence codes from the Evidence and Conclusion Ontology (ECO) which can be used to determine if an annotation is curated from experimental data or generated by an automated method [14, 15]. While the GO section is about gene product function, the “Protein Families, Domains and Sites” section provides links to additional resources where further information about protein products of the gene can be obtained.…”