Survival analysis is a cornerstone of medical research enabling the assessment of clinical outcome for disease progression and treatment efficiency. Despite its central importance, neither commonly used spreadsheet software can handle it nor is there a web server for its computation.
Here we introduce a web-based tool capable to perform uni- and multivariate Cox proportional hazards survival analysis using data generated by genomic, transcriptomic, proteomic, or metabolomics studies.
We implemented different methods to establish cutoff values for trichotomization or for the dichotomization of continuous data. False discovery rate is computed to correct for multiple hypothesis testing. Multivariate analysis option enables comparing omics data with clinical variables.
The registration-free web-service is available at https://kmplot.com/custom_data.
The tool fills a gap and will be an invaluable help for basic medical and clinical research.