Differential analysis of genomics count data with edge*
Abstract
Abstract The edgeR Bioconductor package is one of the most widely used tools for differential expression analysis of count-based genomics data. Despite its popularity, the R-only implementation limits its integration with the Python-centric ecosystem that has become dominant in single-cell genomics. We present edgePython, a Python port of edgeR 4.8.2 that extends the framework with a negative binomial–gamma mixed model for multi-subject single-cell analysis and empirical Bayes shrinkage of cell-level dispersion.
Fields of Study & Subjects
Single-cell and spatial transcriptomics
Gene expression and cancer classification
Gene Regulatory Network Analysis
Publication details
- Journal / source
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Publication date
- 18 February 2026
- Document type
- Preprint