UltraSur: A Versatile Survival Analysis Tool for Multi-Omics Data in Cancer Research
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Background: Survival analysis is fundamental to translational oncology for identifying prognostic biomarkers and therapeutic targets. Despite numerous web-based tools, current platforms face critical limitations: restricted data compatibility (often single-omics only) and lack of analytical flexibility. These constraints impede biomedical researchers and clinicians lacking advanced computational expertise from extracting robust, clinically actionable insights from complex datasets. Results: We developed UltraSur, a comprehensive platform accommodating heterogeneous molecular data. Its core innovation is a dual continuous variable analysis capability: 1. Manual definition of clinically relevant thresholds. 2. Automated determination of statistically optimized cutoffs using maximally selected rank statistics. UltraSur integrates multi-omics data from The Cancer Genome Atlas (TCGA) and supports user-customized dataset upload, enabling flexible analysis across experimental and clinical contexts. UltraSur overcomes the rigidity of existing tools by enabling analysis beyond predefined grouping methods and single-omics data. It uniquely provides both manual and statistically optimized threshold determination strategies. The platform successfully integrates TCGA multi-omics data with user-provided data, facilitating hypothesis-free exploration. Conclusions: UltraSur significantly enhances translational oncology research by providing broad analytical flexibility. It ensures wide applicability, particularly for biomarker discovery and therapeutic target prioritization. By democratizing sophisticated survival analysis, UltraSur accelerates the extraction of clinically actionable insights from complex datasets.
