GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Open accessAbstract
BACKGROUND: Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results. RESULTS: GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms. CONCLUSION: GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at: http://cbl-gorilla.cs.technion.ac.il
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GO term analysis indicated significant enrichment of only one process: regulators of calcineurin (CNB1, RCN1).
“GO term analysis (33) indicated significant enrichment of only one process (P-value = 5.2E-5; false discovery rate = 6.3E-2): regulators of calcineurin (CNB1, RCN1), a well-studied Ca2+/calmodulin-dependent protein phosphatase.”
From Echinocandin tolerance and persistence <i>in vitro</i> are regulated by calcineurin signaling in <i>Candida glabrata</i> (2026) · cites this paper as [33]
GOrilla analysis identified 13 functional super categories.
“We employed GOrilla (Eden et al. , 2009) on the genes ranked according to the LFC along the genotype -axis and along the Aβ -axis, and identified 13 functional super categories (Figure S3A, Table S2).”
From Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer’s Disease (2020) · cites this paper as Eden et al., 2009
Embryonic epithelia upregulated genes for developmental processes, while aged epithelia upregulated host-defense programs.
“These were enriched for specialized programs across ages: Embryonic epithelia upregulated genes for developmental processes (Figure 3K, S3K), while aged epithelia upregulated host-defense programs (Figure 3L, FDR q-value < 0.01, GOrilla (Eden et al., 2007, 2009;Baruch et al., 2014).”
From A cellular and spatial map of the choroid plexus across brain ventricles and ages (2021) · cites this paper as Eden et al., 2009
Biological ontologies are large hierarchies with a DAG structure, so existing tools for visualizing ontologies can have direct application to data-driven multiscale models.
“Biological ontologies are large hierarchies which also have a DAG structure; as such, existing tools for visualizing ontologies can also have direct application to data-driven multiscale models (Binns et al., 2009; Eden et al., 2009; Sealfon et al., 2006; Supek et al., 2011; Zhu et al., 2019).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Eden et al., 2009
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- Authors
- Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z.
- Affiliations
- Weizmann Institute of Science (IL)
- Tel Aviv University (IL)
- Technion – Israel Institute of Technology (IL)
- Corresponding author
- Eden, Eran
- Navon, Roy
- Venue
- BMC Bioinformatics
- Published
- 2009-02-03
- Volume
- 10
- Issue
- 1
- Pages
- 48-48
- ISSN
- 1471-2105 (ISSN-L)
- PMC
- PMC2644678
- OpenAlex
- W2038963685
- Cited by
- 3,356
- References
- 20
- Citations by year
- 2026: 64 · 2025: 135 · 2024: 169 · 2023: 213 · 2022: 274 · 2021: 409 · 2020: 305 · 2019: 319 · 2018: 300 · 2017: 251 · 2016: 242 · 2015: 217 · 2014: 168 · 2013: 138 · 2012: 67
- FWCI
- 20.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Bioinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- European Commission
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Keywords
- gorillas, gene ontology enrichment, exact p-values, web-based bioinformatics tool, differential gene expression
- MeSH terms
- Algorithms, Animals, Data Interpretation, Statistical, Genes, Humans, Models, Genetic, Terminology as Topic, Software, User-Computer Interface, Yeasts, Models, Statistical, Information Storage and Retrieval, Arabidopsis, Computational Biology, Internet, Gene Expression Profiling, Genomics, Databases, Genetic
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