In the last decade, single-cell RNA sequencing routinely performed on large numbers of
single cells has greatly advanced our understanding of the underlying heterogeneity of …

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 …

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

The paired measurement of RNA and surface proteins in single cells with cellular indexing
of transcriptomes and epitopes by sequencing (CITE-seq) is a promising approach to …

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 …

We perform a thorough analysis of RNA velocity methods, with a view towards
understanding the suitability of the various assumptions underlying popular …

An explosion in single-cell technologies has revealed a previously underappreciated
heterogeneity of cell types and novel cell-state associations with sex, disease, development …

Multi-omic single-cell datasets, in which multiple molecular modalities are profiled within the
same cell, offer an opportunity to understand the temporal relationship between epigenome …

Background The rapid development of single-cell RNA-sequencing (scRNA-seq)
technologies has led to the emergence of many methods for removing systematic technical …

RNA velocity provides an approach for inferring cellular state transitions from single-cell
RNA sequencing (scRNA-seq) data. Conventional RNA velocity models infer universal …