The rapid progress of protocols for sequencing single-cell transcriptomes over the past
decade has been accompanied by equally impressive advances in the computational …

The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize
cellular heterogeneity. However, scRNA-seq requires lysing cells, which impedes further …

Computational trajectory inference enables the reconstruction of cell state dynamics from
single-cell RNA sequencing experiments. However, trajectory inference requires that the …

RNA velocity has opened up new ways of studying cellular differentiation in single-cell RNA-
sequencing data. It describes the rate of gene expression change for an individual gene at a …

A fundamental goal of developmental and stem cell biology is to map the developmental
history (ontogeny) of differentiated cell types. Recent advances in high-throughput single …

The recent maturation of single-cell RNA sequencing (scRNA-seq) technologies has
coincided with transformative new methods to profile genetic, epigenetic, spatial, proteomic …

High-throughput single-cell profiling provides an unprecedented ability to uncover the
molecular states of millions of cells. These technologies are, however, destructive to cells …

Understanding the molecular programs that guide differentiation during development is a
major challenge. Here, we introduce Waddington-OT, an approach for studying …

Studies with temporal or spatial resolution are crucial to understand the molecular dynamics
and spatial dependencies underlying a biological process or system. With advances in high …