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Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups.
Wiebe, Daniil S; Omelyanchuk, Nadezhda A; Mukhin, Aleksei M; Grosse, Ivo; Lashin, Sergey A; Zemlyanskaya, Elena V; Mironova, Victoria V.
Afiliación
  • Wiebe DS; Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences (SB RAS), 630090 Novosibirsk, Russia.
  • Omelyanchuk NA; Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences (SB RAS), 630090 Novosibirsk, Russia.
  • Mukhin AM; Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences (SB RAS), 630090 Novosibirsk, Russia.
  • Grosse I; Institute of Computer Science, Martin Luther University Halle-Wittenberg, 06120 Halle, Germany.
  • Lashin SA; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany.
  • Zemlyanskaya EV; Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences (SB RAS), 630090 Novosibirsk, Russia.
  • Mironova VV; LCT & EB, Faculty of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia.
Genes (Basel) ; 11(4)2020 04 17.
Article en En | MEDLINE | ID: mdl-32316383
ABSTRACT
Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes from transcriptome data with respect to their fold changes. FSEA identifies Gene Ontology (GO) terms, which are shared by the group of genes with a similar magnitude of response, and assesses these changes. GO terms found by FSEA are fold-change-specifically (e.g., weakly, moderately, or strongly) affected by a stimulus under investigation. We demonstrate that many responses to abiotic factors, mutations, treatments, and diseases occur in a fold-change-specific manner. FSEA analyses suggest that there are two prevailing responses of functionally-related gene groups, either weak or strong. Notably, some of the fold-change-specific GO terms are invisible by classical algorithms for functional gene enrichment, Singular Enrichment Analysis (SEA), and Gene Set Enrichment Analysis (GSEA). These are GO terms not enriched compared to the genome background but strictly regulated by a factor within specific fold-change intervals. FSEA analysis of a cancer-related transcriptome suggested that the gene groups with a tightly coordinated response can be the valuable source to search for possible regulators, markers, and therapeutic targets in oncogenic processes. Availability and Implementation FSEA is implemented as the FoldGO Bioconductor R package and a web-server.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Biomarcadores / Biología Computacional / Perfilación de la Expresión Génica / Transcriptoma / Ontología de Genes Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Biomarcadores / Biología Computacional / Perfilación de la Expresión Génica / Transcriptoma / Ontología de Genes Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article