Winship Biostatistics and Bioinformatics Shiny Server

Biostatistics and Bioinformatics Applications for Cancer Research

Integrated Genomic Analysis of:
- Genes using GISPA
- Samples using SISPA
- Gene Outliers using G-OPEA
Clustering Analysis with NOJAH
Supervised Principle Component Analysis with GAC
Survival Analysis with CASAS
Exploratory Analysis with shinyEA

Supervised Principle Component Analysis (SuperPC):

Gene Associations with Clinical (GAC)

How to define features (e.g., genes) associated with clinical outcome when you have BIG DATA and small sample size?

With GAC, you can use:

Any outcome data
Any type of BIG data (e.g., gene expression)

With GAC, you can define:

Features associated with clinical outcome.
Forest plot summarizing feature associations with clinical.

http://bbisr.shinyapps.winship.emory.edu/GAC/

Publication:
Zhang X, Rupji M and Kowalski J. GAC: Gene Associations with Clinical, a web based application [version 3; referees: 2 approved, 1 approved with reservations]. F1000Research 2018, 6:1039 (doi: 10.12688/f1000research.11840.3)

https://f1000research.com/articles/6-1039/v3