DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis
| Autor: | Qing-Yu He, Li-Gen Wang, Guang-Rong Yan, Guangchuang Yu |
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| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
Computer science Context (language use) Computational biology computer.software_genre Biochemistry Bioconductor Set (abstract data type) Disease Ontology Databases Genetic Humans Relevance (information retrieval) Disease Molecular Biology Gene Biological data Computational Biology Computer Science Applications Semantics Computational Mathematics Gene Ontology Computational Theory and Mathematics Multigene Family Human genome Programming Languages Data mining computer Software |
| Zdroj: | Bioinformatics (Oxford, England). 31(4) |
| ISSN: | 1367-4811 |
| Popis: | 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 |
| Databáze: | OpenAIRE |
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