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DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis.
Yu, Guangchuang; Wang, Li-Gen; Yan, Guang-Rong; He, Qing-Yu.
Afiliação
  • Yu G; 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
  • Wang LG; 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
  • Yan GR; 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
  • He QY; 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
Bioinformatics ; 31(4): 608-9, 2015 Feb 15.
Article em En | MEDLINE | ID: mdl-25677125
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Semântica / Linguagens de Programação / Software / Doença / Biologia Computacional / Ontologia Genética Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Semântica / Linguagens de Programação / Software / Doença / Biologia Computacional / Ontologia Genética Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2015 Tipo de documento: Article