ArticleScientific reports2022
Survival Genie, a web platform for survival analysis across pediatric and adult cancers.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed, 86 citations in OpenAlex.
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- Targeting CCR1 Remodels the Tumor Microenvironment and Relieves Immunosuppression in Pancreatic Cancer.Cancer immunology research · 2026Article
- Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.Genome biology · 2026Article
- Article
- Survival Genie 2: a next-generation web server for targeted and single-cell-based survival analyses.Genome medicine · 2026Article
- Targeting WNK1 Releases Differentiation Block in Acute Myeloid Leukemia.bioRxiv : the preprint server for biology · 2026Article
- LIN28A-Dependent Kinome and Phosphoproteome Reprogramming Promotes Imatinib Resistance.Molecular & cellular proteomics : MCP · 2026Article
- Epigenetic remodeling via HDAC6 inhibition amplifies anti-tumoral immune responses in myeloid leukemia cells.Cell death & disease · 2026Article
- Inherited resilience to clonal hematopoiesis by modifying stem cell RNA regulation.Science (New York, N.Y.) · 2026Article
- Pan-cancer molecular signatures connecting aspartate transaminase to cancer prognosis, metabolic and immune signatures.Frontiers in oncology · 2026Article
- Comprehensive characterization of AP-1 adaptor complex genes in lung cancer reveals AP1AR as a novel prognostic and therapeutic biomarker.Journal of Cancer · 2026Article
- Leveraging the active conformation of LFA-1 as a potential target for hematological malignancies.Molecular therapy. Methods & clinical development · 2025Article
- Senolytic-sensitive p16Cell stem cell · 2025Article
- Genetic variation reveals a homeotic long noncoding RNA that modulates human hematopoietic stem cells.bioRxiv : the preprint server for biology · 2025Article
- Artificial intelligence approaches for tumor phenotype stratification from single-cell transcriptomic data.eLife · 2025Article
- Identification of leukemia-enriched signature through the development of a comprehensive pediatric single-cell atlas.Nature communications · 2025Article
- In silico pan-cancer analysis of VRAC subunits and their prognostic roles in human cancers.Scientific reports · 2025Article
- Immune evasion mechanisms in early-stage I high-grade serous ovarian carcinoma: insights into regulatory T cell dynamics.Cell death & disease · 2025Article
- Loss of NF1 Accelerates Uveal and Intradermal Melanoma Tumorigenesis, and Oncogenic GNAQ Transforms Schwann Cells.Cancer research communications · 2025Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
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 gene expression/mutations to the clinical outcome but lack the ability to perform 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 remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile. The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/ .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.