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Resource: A curated database of brain-related functional gene sets (Brain.GMT).
Hagenauer, Megan H; Sannah, Yusra; Hebda-Bauer, Elaine K; Rhoads, Cosette; O'Connor, Angela M; Flandreau, Elizabeth; Watson, Stanley J; Akil, Huda.
Afiliación
  • Hagenauer MH; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA.
  • Sannah Y; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA.
  • Hebda-Bauer EK; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA.
  • Rhoads C; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA.
  • O'Connor AM; National Institutes of Health, Bethesda, MD 20892, USA.
  • Flandreau E; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA.
  • Watson SJ; Grand Valley State University, Allendale, MI 49401, USA.
  • Akil H; Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA.
MethodsX ; 13: 102788, 2024 Dec.
Article en En | MEDLINE | ID: mdl-39049932
ABSTRACT
Transcriptional profiling has become a common tool for investigating the nervous system. During analysis, differential expression results are often compared to functional ontology databases, which contain curated gene sets representing well-studied pathways. This dependence can cause neuroscience studies to be interpreted in terms of functional pathways documented in better studied tissues (e.g., liver) and topics (e.g., cancer), and systematically emphasizes well-studied genes, leaving other findings in the obscurity of the brain "ignorome". To address this issue, we compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT") that can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret results from three species (rat, mouse, human). Brain.GMT includes brain-related gene sets curated from the Molecular Signatures Database (MSigDB) and extracted from public databases (GeneWeaver, Gemma, DropViz, BrainInABlender, HippoSeq) and published studies containing differential expression results. Although Brain.GMT is still undergoing development and currently only represents a fraction of available brain gene sets, "brain ignorome" genes are already better represented than in traditional Gene Ontology databases. Moreover, Brain.GMT substantially improves the quantity and quality of gene sets identified as enriched with differential expression in neuroscience studies, enhancing interpretation. •We compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT").•Brain.GMT can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret neuroscience transcriptional profiling results from three species (rat, mouse, human).•Although Brain.GMT is still undergoing development, it substantially improved the interpretation of differential expression results within our initial use cases.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MethodsX Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MethodsX Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos