PESSA
PESSA (Pathway Enrichment Score-based Survival Analysis) is a large-scale interactive web tool dedicated to pan-cancer survival analysis and visualization by using results from single sample gene set enrichment analysis(ssGSEA). With PESSA, users can quickly explore the impact of target pathway on survival outcomes in different tumors, assisting clinicians and researchers in further investigating the mechanism of tumor development and improving clinical decision-making.
PESSA is accessible at: https://smuonco.shinyapps.io/PESSA/ and http://robinl-lab.com/PESSA
How does PESSA work?
STEP1: Select Data to Be Processed
STEP2: View Analysis Results
STEP3: Costomize and Download Your Plot
Updates
20/03/23 Version 1.0.0 of PESSA released.
08/02/24 Version 1.1.0 of PESSA released.
STEP1: Select Data to Be Processed
Brief Description
For more information, please refer to the website
STEP2: View Analysis Results
STEP3: View, Costomize and Download Your Plot
DATASETS DESCRIPTION
Contact
Should you have any questions, please feel free to contact us.
Peng Luo: luopeng@smu.edu.cn
Hong Yang: smuyanghong@i.smu.edu.cn
Ying Shi: shoshanashi@i.smu.edu.cn
Our lab has a long-standing interest in cancer biomedical research and bioinformatics. We recently developed several other Shiny web tools focusing on solving various scientific questions.
PanCanSurvPlot: A Web Server for Pan-cancer Transcriptome Survival Analysis and Visualization. doi: 10.1101/2022.12.25.521884[preprint]
Citation: Lin, A., Yang, H., Shi, Y., Cheng, Q., Liu, Z., Zhang, J., & Luo, P. (2022). PanCanSurvPlot: A Large-scale Pan-cancer Survival Analysis Web Application. BioRxiv, 2022.12.25.521884. https://doi.org/10.1101/2022.12.25.521884
CAMOIP: A Web Server for Comprehensive Analysis on Multi-omics of Immunotherapy in Pan-cancer. doi: 10.1093/bib/bbac129
Citation: Lin, A., Qi, C., Wei, T., Li, M., Cheng, Q., Liu, Z., Luo, P., & Zhang, J. (2022). CAMOIP: a web server for comprehensive analysis on multi-omics of immunotherapy in pan-cancer. Briefings in Bioinformatics, 23(3). https://doi.org/10.1093/bib/bbac129
Onlinemeta: A Web Server for Meta-Analysis Based On R-shiny. doi: 10.1101/2022.04.13.488126[preprint]
Citation: Yi, Y., Lin, A., Zhou, C., Jian, Z., Wang, S., & Luo, P. (2022). Onlinemeta: A Web Serve For Meta-Analysis Based On R-shiny. BioRxiv, 2022.04.13.488126. https://doi.org/10.1101/2022.04.13.488126
Tutorial Video
For users who can not access, the tutorial video is also available on Bilibili.
Comment Box
Update History
20/03/23 Version 1.0.0beta of PESSA released.
08/02/24 Version 1.1.0beta of PESSA released.
FAQ
1. Why does the gene sets I type in return no results?
The gene sets we provided here mostly come from MSigDB(HGNC-approved) Hallmark gene sets, Canonical pathways and Gene Ontology gene sets. The whole list of gene sets we provided can be found here.
2. What are the full forms of the survival outcomes provided?
Altogether, there are 13 different survival outcomes available. Their abbreviations and corresponding full forms are shown below.
BCR: Biochemical Recurrence Free Survival
CSS: Cancer Specific Survival
DFI: Disease Free Interval
DFS: Disease Free Survival
DMFS: Distant Metastasis Free Survival
DRFS: Distant Relapse Free Survival
DSS: Disease Specific Survival
FFS: Failure Free Survival
MFS: Metastasis Free Survival
OS: Overall Survival
PFI: Progression Free Interval
PFS: Progression Free Survival
RFS: Recurrence Free Survival
3. Why is there no median survival line shown in the K-M plot I have made?
Because of the specific cutoff point you chose, the median survival has not yet been reached, and more than half of the patients are still alive.