Background Single-cell transcriptomics allows researchers to investigate complex
communities of heterogeneous cells. It can be applied to stem cells and their descendants in …

Subpopulation identification, usually via some form of unsupervised clustering, is a
fundamental step in the analysis of many single-cell RNA-seq data sets. This has motivated …

As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the
number of tools designed to analyse these data has dramatically increased. Navigating the …

Single-cell RNA sequencing (scRNA-seq) is currently transforming our understanding of
biology, as it is a powerful tool to resolve cellular heterogeneity and molecular networks …

Background: Single-cell RNA-seq is a powerful tool for measuring gene expression at the
resolution of individual cells. A challenge in the analysis of this data is the large amount of …

When different types of functional genomics data are generated on single cells from different
samples of cells from the same heterogeneous population, the clustering of cells in the …

Single-cell RNA-sequencing (scRNA-seq) is a recent breakthrough technology, which paves
the way for measuring RNA levels at single cell resolution to study precise biological …

Abstract The Human Cell Atlas is a large, international consortium that aims to identify and
describe every cell type in the human body. The comprehensive cellular maps that arise …

Single cell messenger RNA sequencing (scRNA-seq) provides a window into transcriptional
landscapes in complex tissues. The recent introduction of droplet based transcriptomics …

A better understanding of the cell-fate transitions that occur in complex cellular ecosystems
in normal development and disease could inform cell engineering efforts and lead to …