Salvato in:
| Autore principale: | |
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| Natura: | Recurso digital |
| Lingua: | inglese |
| Pubblicazione: |
Zenodo
2026
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| Soggetti: | |
| Accesso online: | https://doi.org/10.5281/zenodo.19966788 |
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Sommario:
- <p>This study investigates whether patient-level gene expression dispersion (coefficient of variation, CV) represents a biologically meaningful survival signal or an emergent statistical property of high-dimensional data. Using TCGA glioblastoma (GBM), the CV metric significantly stratifies survival. However, systematic falsification—including random gene controls, permutation-based structure destruction, cross-cancer testing, network analysis, spectral decomposition, predictive validation, and high-dimensional geometry—demonstrates that the signal is context-dependent, non-generalizable, weakly predictive, and not supported by pathway or network structure. These findings show that survival signals can arise from aggregation effects in high-dimensional systems and emphasize the need for structural validation in omics research.</p>