Single-cell RNA sequencing (scRNA-seq) is widely used to characterize cell types based on their average gene expression profiles, however most studies do not consider cell type-specific variation across individuals. Here the authors introduce a model to study cell type-specificity of inter-individual variation in scRNA-seq data and show that it can identify biologically meaningful signals missed by conventional differential expression tests.
