@haojiawu @biorxivpreprint this is very interesting. I have been telling people that one of the main reasons for using #RStats instead of #python for gene expression analysis, is the lack of methods such as #DESeq2 or #limma as python libraries. This might tip the balance for a lot of people.

Of course there are many reasons to prefer R, the excellent #Bioconductor ecosystem one of them, and in fairness, for #scRNA analysis python has very strong ecosystem and community.

@keyboardpipette @biorxivpreprint That's true. There is a python implementation of edgeR too. https://github.com/r-bioinformatics/edgePy
but still less python tools can be seen for bulk RNA-seq analysis.
GitHub - r-bioinformatics/edgePy: A Python implementation of edgeR for differential expression analysis

A Python implementation of edgeR for differential expression analysis - GitHub - r-bioinformatics/edgePy: A Python implementation of edgeR for differential expression analysis

GitHub
@haojiawu @biorxivpreprint yes, but in development and last commit was 4 years ago. So not really an option. It's certainly interesting why there's such an imbalance in number of python libraries for single cell Vs bulk.