Recent experimental developments in genome-wide RNA quantification hold considerable
promise for systems biology. However, rigorously probing the biology of living cells requires …

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

Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their
workflows. Maximizing the potential of scRNA-seq requires a proper understanding of the …

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

Dimensionality reduction is standard practice for filtering noise and identifying relevant
features in large-scale data analyses. In biology, single-cell genomics studies typically begin …

Background Dimensionality reduction is an indispensable analytic component for many
areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality …

Abstract Single-cell RNA-Seq (scRNA-seq) is invaluable for studying biological systems.
Dimensionality reduction is a crucial step in interpreting the relation between cells in scRNA …

Current differentiation protocols have not been successful in reproducibly generating fully
functional human beta cells in vitro, partly due to incomplete understanding of human …

Abstract Two-dimensional (2D) embedding methods are crucial for single-cell data
visualization. Popular methods such as t-distributed stochastic neighbor embedding (t-SNE) …

Efferocytosis triggers cellular reprogramming, including the induction of mRNA transcripts
which encode anti-inflammatory cytokines that promote inflammation resolution. Our current …