An unsupervised tool for biomarker discovery and cancer subtyping applied to glioblastoma

TRIM-IT provides a novel approach for analyzing high-dimensional omics data while preserving key biological insights. Its ability to identify meaningful patient subgroups and molecular signatures highlights its applicability across various biomedical research contexts. The tool is implemented in R and the code is publicly available for reproduction and adaptation to other studies.