Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but
does not capture their spatial distribution nor reveal local networks of intercellular …

Single-cell RNA sequencing (scRNA-seq) technologies allow the dissection of gene
expression at single-cell resolution, which greatly revolutionizes transcriptomic studies. A …

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

Abstract Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells.
Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using …

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 …

Advances in single-cell RNA sequencing (scRNA-seq) technologies in the past 10 years
have had a transformative effect on biomedical research, enabling the profiling and analysis …

Thanks to innovative sample-preparation and sequencing technologies, gene expression in
individual cells can now be measured for thousands of cells in a single experiment. Since its …

Natural killer (NK) cells are critical to both innate and adaptive immunity. However, the
development and heterogeneity of human NK cells are yet to be fully defined. Using single …

Background A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately
detect the number of cell types in the sample, which can be critical for downstream analyses …

The recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a
large variety of experimental and computational pipelines for which best practices have not …