Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly
evolving, making it possible to comprehensively characterize cells and tissues in health and …

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

Background Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple
sources, including biological variation in cellular state as well as technical variation …

The high-dimensional data created by high-throughput technologies require visualization
tools that reveal data structure and patterns in an intuitive form. We present PHATE, a …

Single‐cell RNA‐seq has enabled gene expression to be studied at an unprecedented
resolution. The promise of this technology is attracting a growing user base for single‐cell …

Recent technological advancements have enabled the profiling of a large number of
genome-wide features in individual cells. However, single-cell data present unique …

As the number of single‐cell transcriptomics datasets grows, the natural next step is to
integrate the accumulating data to achieve a common ontology of cell types and states …

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

To the Editor—Potential users of single-cell RNA-sequencing (scRNA-seq) 1 often
encounter a choice between highthroughput droplet-based methods and high-sensitivity …

Many methods have been used to determine differential gene expression from single-cell
RNA (scRNA)-seq data. We evaluated 36 approaches using experimental and synthetic …