A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.

Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics

Differential expression analysis for single-cell RNA-seq data.

Brings bulk and pseudobulk transcriptomics to the tidyverse

MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics data

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

integrated RNA-seq Analysis Pipeline

Porting DESeq2 into python via rpy2

A Snakemake workflow for differential expression analysis of RNA-seq data with Kallisto and Sleuth.

Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq

R package for pathway analysis in scRNA-seq data

Compare different differential abundance and expression methods

Explore and share your scRNAseq clustering results

Experimental design framework for scRNAseq population studies (eQTL and DE)

Best practice RNA-Seq analysis pipeline for reference-based RNA-Seq analysis

An R package to plot interactive three-way differential expression analysis

UNDER DEVELOPMENT--- Analysis of long non-coding RNAs from RNA-seq datasets

Interactive Differential Expression AnaLysis - DE made accessible and reproducible

Fit generalized linear models in python.

pseudobulking on an AnnData object