Gene Ontology annotation quality analysis in model eukaryotes

Buza, Teresia; McCarthy, Fiona M.; Wang, Nan; Bridges, Susan M.; Burgess, Shane C.

doi:10.1093/nar/gkm1167

Cited by 45 publications

(58 citation statements)

References 13 publications

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“…In life sciences, the quality of annotations especially Gene Ontology annotations including evidence codes has been studied in [6,12,22]. Particularly, the case study in [6] assesses annotation quality by using quality-scores for ECs thereby the scores are intuitively defined by the authors. They show descriptive and comparative statistics w.r.t.…”

Section: Related Workmentioning

confidence: 99%

Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

Groß

Hartung

Kirsten

et al. 2009

Lecture Notes in Computer Science

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Abstract. Ontology-based annotations associate objects, such as genes and proteins, with well-defined ontology concepts to semantically and uniformly describe object properties. Such annotation mappings are utilized in different applications and analysis studies whose results strongly depend on the quality of the used annotations. To study the quality of annotations we propose a generic evaluation approach considering the annotation generation methods (provenance) as well as the evolution of ontologies, object sources, and annotations. Thus, it facilitates the identification of reliable annotations, e.g., for use in analysis applications. We evaluate our approach for functional protein annotations in Ensembl and Swiss-Prot using the Gene Ontology.

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Section: Related Workmentioning

confidence: 99%

Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

Groß

Hartung

Kirsten

et al. 2009

Lecture Notes in Computer Science

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“…In addition, we used the Gene Ontology Annotation Quality (GAQ) [33] score as a quantitative measure to compare the quality of the assigned functional annotations of the original and re-annotated structural annotations. The GAQ score is a quantitative measure of the functional annotation quality.…”

Section: Methodsmentioning

confidence: 99%

Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

et al. 2010

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One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data.

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“…Furthermore, InterPro scan (Hunter et al, 2009) was run on all protein-coding gene models, and additional GO annotations were inferred with InterPro to GO mapping. Redundant GO annotations were merged according to the GO evidence code rank (Buza et al, 2008). To avoid the inclusion of obsolete GO terms, a filter was applied using the set of valid GO terms derived from http://geneontology.org (Ashburner et al, 2000).…”

Section: Functional Annotationmentioning

confidence: 99%

Dissecting Plant Genomes with the PLAZA Comparative Genomics Platform

Bel

Proost²,

Wischnitzki³

et al. 2011

Plant Physiology

242

259

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With the arrival of low-cost, next-generation sequencing, a multitude of new plant genomes are being publicly released, providing unseen opportunities and challenges for comparative genomics studies. Here, we present PLAZA 2.5, a userfriendly online research environment to explore genomic information from different plants. This new release features updates to previous genome annotations and a substantial number of newly available plant genomes as well as various new interactive tools and visualizations. Currently, PLAZA hosts 25 organisms covering a broad taxonomic range, including 13 eudicots, five monocots, one lycopod, one moss, and five algae. The available data consist of structural and functional gene annotations, homologous gene families, multiple sequence alignments, phylogenetic trees, and colinear regions within and between species. A new Integrative Orthology Viewer, combining information from different orthology prediction methodologies, was developed to efficiently investigate complex orthology relationships. Cross-species expression analysis revealed that the integration of complementary data types extended the scope of complex orthology relationships, especially between more distantly related species. Finally, based on phylogenetic profiling, we propose a set of core gene families within the green plant lineage that will be instrumental to assess the gene space of draft or newly sequenced plant genomes during the assembly or annotation phase.

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Gene Ontology annotation quality analysis in model eukaryotes

Cited by 45 publications

References 13 publications

Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

Dissecting Plant Genomes with the PLAZA Comparative Genomics Platform

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