The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis
Open accessAbstract
Summary: Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported. Availability and implementation: DOSE is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/DOSE.html). Supplementary information: Supplementary Data are available at Bioinformatics online. Contact: gcyu@connect.hku.hk or tqyhe@jnu.edu.cn
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Cites
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
Self-citationA new method to measure the semantic similarity of GO terms
Wang, J. Z., Du, Z., Payattakool, R., Yu, P. S., & Chen, C.-F. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm087 · Cited by 1,377
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ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization
Yu, G., & He, Q.-Y. (2015) · Molecular BioSystems · doi:10.1039/c5mb00663e · Cited by 1,918
Self-citationSingle cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease
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Functional characterization of the dural sinuses as a neuroimmune interface
Rustenhoven, J., Drieu, A., Mamuladze, T., de Lima, K. A., Dykstra, T., Wall, M., Papadopoulos, Z., Kanamori, M., Salvador, A. F., Baker, W., et al. (2021) · Cell · doi:10.1016/j.cell.2020.12.040 · Cited by 685
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Da Mesquita, S., Papadopoulos, Z., Dykstra, T., Brase, L., Farias, F. G., Wall, M., Jiang, H., Kodira, C. D., de Lima, K. A., Herz, J., et al. (2021) · Nature · doi:10.1038/s41586-021-03489-0 · Cited by 431
Metadata
- Authors
- Yu, G., Wang, L.-G., Yan, G.-R., & He, Q.-Y.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-10-17
- Volume
- 31
- Issue
- 4
- Pages
- 608-609
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2140099276
- Cited by
- 1,274
- References
- 2
- FWCI
- 5.96
- Type
- journal article
- Language
- en
- Open access
- bronze
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