A web portal for single-cell data, gene-ratio, and cell composition-based survival analyses

The genomics data-driven identification of gene signatures, and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate expression or mutations of a gene to clinical outcome, but lack on performing such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remains an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates associations between the enrichment of canonical cell types and survival outcome across cancers.

Here we developed Survival Genie, an interactive R shiny tool to correlate gene sets, pathways, cellular enrichment and single cell signatures to clinical outcome to assist in developing next generation prognostic and therapeutic biomarkers.

The analytical options and comprehensive collection of cancer datasets makes Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment and single cell signatures to clinical outcome to assist in developing next generation prognostic and therapeutic biomarkers.

Survival Genie is implemented in R shiny and is available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/ and https://bhasinlab.bmi.emory.edu/SurvivalGenie

A step by step guide on using the tutorial can be found here.

The YouTube video for the tutorial can be accessed by clicking on the below thumbnail.