DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis

doi:10.1093/bioinformatics/btu684

. 2015 Feb 15;31(4):608-9.

doi: 10.1093/bioinformatics/btu684. Epub 2014 Oct 17.

DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis

Guangchuang Yu¹, Li-Gen Wang², Guang-Rong Yan², Qing-Yu He²

Affiliations

¹ State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.
² State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.

PMID: 25677125
DOI: 10.1093/bioinformatics/btu684

DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis

Guangchuang Yu et al. Bioinformatics. 2015.

. 2015 Feb 15;31(4):608-9.

doi: 10.1093/bioinformatics/btu684. Epub 2014 Oct 17.

Authors

Guangchuang Yu¹, Li-Gen Wang², Guang-Rong Yan², Qing-Yu He²

Affiliations

¹ State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.
² State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632 and Guangdong Information Center, Guangzhou 510031, China.

PMID: 25677125
DOI: 10.1093/bioinformatics/btu684

Abstract

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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DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis

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DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis

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