MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis

• Published in: BMC bioinformatics Vol. 16; no. 1; p. 45
• Main Authors: Tsuyuzaki, Koki, Morota, Gota, Ishii, Manabu, Nakazato, Takeru, Miyazaki, Satoru, Nikaido, Itoshi
• Format: Journal Article
• Language: English
• Published: London BioMed Central 15.02.2015; BioMed Central Ltd
• Subjects: Algorithms; Animals; Bioinformatics; Biomedical and Life Sciences; Caloric Restriction; Computational Biology - methods; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Gene Expression Profiling; Genome-Wide Association Study; Humans; Information Storage and Retrieval - methods; Knowledge-based analysis; Life Sciences; Medical Subject Headings; Microarrays; Molecular Sequence Annotation; Oligonucleotide Array Sequence Analysis; Pseudomonas aeruginosa - genetics; PubMed; Rats; Software; Vocabulary, Controlled; MeSH; Over-representation analysis; Enrichment analysis; Annotation
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-015-0453-z

Background In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons. Results In this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db , MeSH.AOR.db , MeSH.PCR.db , the org.MeSH.XXX.db -type packages, MeSHDbi , and meshr . Conclusions Using our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework.