Differential analysis of genomics count data with edge*
Pachter, L.
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.
Lior Pachter, with a sprinkle of AI wizardry from Claude and Codex, teleports the venerable edgeR from R to Python in a mere week, birthing edgePython that jazzes up single-cell analysis with Empirical Bayes flair, leaving bioinformatic glitches in the dust.
Posted by computational biologist Lior Pachter (@lpachter) with notes on the AI-assisted porting process, sparking code critiques from Uria Mor (@uria_mor), humorous jabs like "But does it make UMAPs?" from David Garfield (@dagarfield), and calls to port more tools from Chris Rands (@c_rands)
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