Joshua D. Welch

TL;DR: Slide-seq provides a scalable method for obtaining spatially resolved gene expression data at resolutions comparable to the sizes of individual cells, and defines the temporal evolution of cell type–specific responses in a mouse model of traumatic brain injury.

TL;DR: LIGER, an algorithm that delineates shared and dataset-specific features of cell identity, was applied to four diverse and challenging analyses of human and mouse brain cells, revealing putative mechanisms of cell-type-specific epigenomic regulation.

TL;DR: This study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps, and establishes a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

TL;DR: The developed SLICER (Selective Locally Linear Inference of Cellular Expression Relationships) can infer highly nonlinear trajectories, select genes without prior knowledge of the process, and automatically determine the location and number of branches and loops.

TL;DR: Single-cell transcriptomics approaches enabled us to reconstruct the reprogramming trajectory and to uncover intermediate cell populations, gene pathways and regulators involved in iCM induction.