name description
GO_BP Gene Ontology Biological processes
GO_CC Gene Ontology cellular components
GO_MF Gene Ontology molecular functions
GSEA_H Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes). Hallmark gene sets in particular summarize and represent specific well-defined biological states or processes and display coherent expression. These gene sets were generated by a computational methodology based on identifying gene set overlaps and retaining genes that display coordinate expression. The hallmarks reduce noise and redundancy and provide a better delineated biological space for GSEA.
DO The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts through collaborative efforts of researchers at Northwestern University, Center for Genetic Medicine and the University of Maryland School of Medicine, Institute for Genome Sciences. The Disease Ontology semantically integrates disease and medical vocabularies through extensive cross mapping of DO terms to MeSH, ICD, NCI’s thesaurus, SNOMED and OMIM. The gene-DO term association are obtained from DISEASES (S Pletscher-Frankild et al, 2015, doi:10.1016/j.ymeth.2014.11.020). DISEASES is a system for extracting disease–gene associations from biomedical abstracts consisting of of a highly efficient dictionary-based tagger for named entity recognition of human genes and diseases. This was combine with a scoring scheme that takes into account co-occurrences both within and between sentences.
HP Human Phenotypes