NEBULA is a fast negative binomial mixed model for differential or co-expression analysis of large-scale multi-subject single-cell data

Abstract

The application of negative binomial mixed models (NBMMs) to single-cell data is computationally demanding. To address this issue, Liang He et al. have developed NEBULA, an efficient algorithm that can analyze differential gene expression or co-expression networks in multi-subject single-cell data sets, and validate it on snRNA-seq and scRNA-seq data sets comprising ~200k cells from cohorts of Alzheimer’s disease and multiple sclerosis patients.