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Анализ на обогатяване на генни набори по Бейсов метод×Мултиомиксен анализ на обогатяване на генни набори×
ОбластБиоинформатикаБиоинформатика
СемействоProcess / pipelineProcess / pipeline
Година на възникване2004–20072005 (GSEA foundation); multi-omics extensions ~2013–2020
СъздателMichael A. Newton, Frank A. Quintana and colleagues; building on Subramanian et al. GSEA frameworkExtended from Subramanian et al. (2005); multi-omics integration formalized ~2010s
ТипProbabilistic gene set enrichment methodIntegrative enrichment analysis pipeline
Основополагащ източникSubramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., ... & Mesirov, J. P. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43), 15545-15550. DOI ↗Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., & Mesirov, J. P. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43), 15545–15550. DOI ↗
Други названияBayesian GSEA, BGSEA, Bayesian pathway scoring, probabilistic gene set testingmulti-omics GSEA, integrated GSEA, cross-omics pathway enrichment, multi-layer GSEA
Свързани66
РезюмеBayesian gene set enrichment analysis (Bayesian GSEA) applies a probabilistic framework to determine whether predefined sets of genes — representing biological pathways, cellular processes, or functional categories — are collectively more differentially expressed than expected by chance. Unlike classical frequentist GSEA, the Bayesian approach models uncertainty in expression estimates explicitly, incorporates prior biological knowledge, and produces posterior probabilities of enrichment rather than raw p-values, enabling more principled inference especially in small-sample settings.Multi-omics gene set enrichment analysis (multi-omics GSEA) is a computational pipeline that applies GSEA logic simultaneously across two or more molecular measurement layers — such as transcriptomics, proteomics, and metabolomics — to identify biological pathways or gene sets that are coordinately dysregulated across omics platforms. By integrating ranked molecular signatures from each layer, it reveals pathway-level convergence that no single omics platform could detect alone.
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ScholarGateСравнение на методи: Bayesian Gene Set Enrichment Analysis · Multi-omics gene set enrichment analysis. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare