Detecting Gene Ontology misannotations using taxon-specific rate ratio comparisons.

ABSTRACT:

Motivation

Many protein function databases are built on automated or semi-automated curations and can contain various annotation errors. The correction of such misannotations is critical to improving the accuracy and reliability of the databases.

Results

We proposed a new approach to detect potentially incorrect Gene Ontology (GO) annotations by comparing the ratio of annotation rates (RAR) for the same GO term across different taxonomic groups, where those with a relatively low RAR usually correspond to incorrect annotations. As an illustration, we applied the approach to 20 commonly studied species in two recent UniProt-GOA releases and identified 250 potential misannotations in the 2018-11-6 release, where only 25% of them were corrected in the 2019-6-3 release. Important

SUBMITTER: Wei X 

PROVIDER: S-EPMC7751014 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature