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Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Analisi di Arricchimento di Insiemi di Geni (GSEA)× | Analisi di Arricchimento di Set di Geni Multi-Omici× | |
|---|---|---|
| Campo | Bioinformatica | Bioinformatica |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 2005 (seminal PNAS paper; predecessor concept in Mootha et al. 2003) | 2005 (GSEA foundation); multi-omics extensions ~2013–2020 |
| Ideatore≠ | Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Jill P. Mesirov, Todd R. Golub, Eric S. Lander et al. (Broad Institute) | Extended from Subramanian et al. (2005); multi-omics integration formalized ~2010s |
| Tipo≠ | Functional genomics / enrichment analysis | Integrative enrichment analysis pipeline |
| Fonte seminale | 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 ↗ | 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 ↗ |
| Alias | GSEA, gene-set analysis, functional enrichment analysis, pathway-level enrichment | multi-omics GSEA, integrated GSEA, cross-omics pathway enrichment, multi-layer GSEA |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether a predefined set of genes — representing a biological pathway, process, or function — shows statistically significant, coordinated differences between two biological conditions. Unlike simple fold-change filtering, GSEA operates on all measured genes ranked by a correlation metric, detecting subtle but consistent shifts across an entire pathway even when no single gene passes a significance threshold. | 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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