Related Experiment Video
Updated: Jun 23, 2026
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
Published on: June 28, 2018
Differentially Expressed Gene Annotator (DEGAn): automated annotation and analysis of DEGs datasets with OS and PFS
Giuseppe Agapito1,2,3,4, Mario Cannataro2,5
1Department of Law, Economics and Sociology, University Magna Græcia of Catanzaro, Catanzaro, 88100, Italy.
Motivation:
High-throughput transcriptomic platforms routinely generate large differentially expressed gene (DEG) datasets, but linking these matrices to clinical outcomes still often requires manual data integration and repeated gene-by-gene survival analyses. This limits scalability, reproducibility, and practical use in translational research.
Results:
We present DEGAn (Differentially Expressed Gene Annotator), a Java-based application for automated survival analysis of DEG matrices annotated with clinical data. DEGAn integrates gene expression with overall survival (OS) and progression-free survival (PFS), performs Kaplan-Meier and log-rank analyses across all genes in a single run, and returns ranked results with false discovery rate correction. The updated version extends DEGAn with configurable stratification strategies, alternative missing-value handling, multi-group survival analysis, and enhanced reporting to support sensitivity assessment and reproducible exploratory screening. DEGAn provides a graphical user interface and is distributed as a standalone executable for local, privacy-preserving analysis.
Availability And Implementation:
DEGAn is implemented in Java and released under the LGPL v3.0+ license. Source code and binaries are available at https://gitlab.com/giuseppeagapito/degan.git.
