SmulTCan: A Shiny application for multivariable survival analysis of TCGA data with gene sets

Survival analysis is widely used in cancer research, and although several methods exist in R, there is the need for a more interactive, flexible, yet comprehensive online tool to analyze gene sets using Cox proportional hazards (CPH) models. The web-based Shiny application (app) SmulTCan extends existing tools to multivariable CPH models of gene sets-as exemplified using the netrins and their receptors (netrins-receptors). It can be used to identify survival gene signatures (GSs) and select the best subsets of input gene, microRNA, methylation level, and copy number variation sets from the Cancer Genome Atlas (TCGA).

To create a tool for CPH model building and best subset selection, using survival data from TCGA with input gene expression files from UCSC Xena. Furthermore, we aim to analyze the input TSV file of netrins-receptors in SmulTCan and discuss our findings.

SmulTCan uses Shiny's reactivity with built-in R functions from packages for CPH model analysis and best subset selection including "survminer", "riskRegression", "rms", "glmnet", and "BeSS".

Results from the SmulTCan app with the netrins-receptors gene set indicated unique hazard ratio GSs in certain renal and neural cancers, while the best subsets for this gene set, obtained via the app, could differentiate between prognostic outcomes in these cancers.

SmulTCan is available at http://konulabapps.bilkent.edu.tr:3838/SmulTCan/. The input file for netrins-receptors is available in the online version of this paper. TCGA dataset folders containing survival files are available through https://github.com/aozh7/SmulTCan/.

The supplementary information (SI) accompanies the online version of this article.