Tran and Shekhar et al. recently used LIGER in their study of neuronal type-specific response to injury10 (link). They focused on the adult mouse retinal ganglion cells (RGCs) and investigated the resilience of RGC types following optic nerve crush (ONC), a common model of traumatic axonal injury. The authors employed scRNA-seq to profile the injured RGCs at different time points post ONC. They used LIGER to develop a common taxonomy of cell types that was robust to time of injury, mouse strain, and batch effects. The capability of LIGER to distinguish shared features such as RGC type-specific expression pattern and dataset-specific features--such as injury-related changes--along the time course enabled discovery of RGC type-specific molecular signatures related to cell resilience and susceptibility to injury.
Additionally, Krienen et al. applied LIGER to probe interneuron cell types and their gene expression patterns across multiple species, including humans, macaques, marmosets, and mice11 (link). The authors used LIGER to jointly define interneuron cell types across species and brain regions from Drop-Seq data. The resulting joint analysis revealed shared cell types across species; an interneuron cell type that appears in humans and monkeys but not mice; and species-specific gene expression differences within shared cell types.
Additionally, Krienen et al. applied LIGER to probe interneuron cell types and their gene expression patterns across multiple species, including humans, macaques, marmosets, and mice11 (link). The authors used LIGER to jointly define interneuron cell types across species and brain regions from Drop-Seq data. The resulting joint analysis revealed shared cell types across species; an interneuron cell type that appears in humans and monkeys but not mice; and species-specific gene expression differences within shared cell types.