keyalone/scDEA: Performing differential expression analysis in single cell RNA sequencing data via ensemble learning

scDEA is an ensemble learning method for differential expression analysis in single cell RNA sequencing data. It ensembles results from multiple individual differential expression analysis methods. The current implementation of scDEA integrates twelve state-of-the-art methods: BPSC, DEsingle, DESeq2, edgeR, MAST, monocle, scDD, T-test, Wilcoxon, limma, Seurat, zingeR.edgeR.

install.packages("remotes")
remotes::install_github("keyalone/scDEA")