Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Bayesian genesettberikelsesanalyse× | Multi-omics gen-settberikningsanalyse× | |
|---|---|---|
| Fagfelt | Bioinformatikk | Bioinformatikk |
| Familie | Process / pipeline | Process / pipeline |
| Opprinnelsesår≠ | 2004–2007 | 2005 (GSEA foundation); multi-omics extensions ~2013–2020 |
| Opphavsperson≠ | Michael A. Newton, Frank A. Quintana and colleagues; building on Subramanian et al. GSEA framework | Extended from Subramanian et al. (2005); multi-omics integration formalized ~2010s |
| Type≠ | Probabilistic gene set enrichment method | Integrative enrichment analysis pipeline |
| Opprinnelig kilde≠ | Subramanian, 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 ↗ |
| Alias | Bayesian GSEA, BGSEA, Bayesian pathway scoring, probabilistic gene set testing | multi-omics GSEA, integrated GSEA, cross-omics pathway enrichment, multi-layer GSEA |
| Relaterte | 6 | 6 |
| Sammendrag≠ | Bayesian 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. |
| ScholarGateDatasett ↗ |
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