Open BiologyBioinformaticsPeer-reviewed journal article
Term Matrix: A novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns
Valerie WoodiD, Seth CarboniD, Midori A. HarrisiD, Antonia LockiD, Stacia R. EngeliD, David P. HilliD, Kimberly M. Van AukeniD, Helen L. AttrilliD, Marc FeuermanniD, Pascale GaudetiD, Ruth C. LoveringiD, Sylvain PouxiD, Kim RutherfordiD, Chris MungalliD
Abstract
Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally, and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes likely reflects errors in literature curation, ontology structure, or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g., amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 2.5 million automatically propagated annotations across all taxa.
- organism: human
- organism: mouse
- organism: yeast
- research focus: benchmarking
- approach: statistical model
- Citations
- 14
- FWCI
- 0.65
- Field percentile
- top 37%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Automatic Consistency Assurance for Literature-based Gene Ontology Annotation
Jiyu Chen, Nicholas Lewis Geard, … Karin M. Verspoor·BMC BioinformaticsPeer-reviewed·Nov 25, 2021
- GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts
Eugene W. Hinderer, Hunter Moseley·PLoS ONEPeer-reviewed·Jun 11, 2020
- Crowdsourcing biocuration: the Community Assessment of Community Annotation with Ontologies (CACAO)
Jolene Ramsey, Brenley K. McIntosh, … James C. Hu·bioRxiv·Apr 30, 2021
- GROOLS: reactive graph reasoning for genome annotation through biological processes
Jonathan Mercier, Adrien Josso, … David Vallenet·BMC BioinformaticsPeer-reviewed·Apr 11, 2018
- Interpretation of biological experiments changes with evolution of Gene Ontology and its annotations
Aurelie Tomczak, Jonathan Mortensen, … Purvesh Khatri·Scientific ReportsPeer-reviewed·Mar 23, 2018
- Novel Comparison of Evaluation Metrics for Gene Ontology Classifiers Reveals Drastic Performance Differences
Ilya Plyusnin, Liisa Holm, Petri Törönen·PLoS Computational BiologyPeer-reviewed·Nov 4, 2019