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

The development of single-cell multimodal assays provides a powerful tool for investigating
multiple dimensions of cellular heterogeneity, enabling new insights into development …

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 reprogramming of somatic cells with defined factors, which converts cells from one
lineage into cells of another, has greatly reshaped our traditional views on cell identity and …

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

Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for
transcriptome-wide analysis of differential gene expression and differential splicing of …

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing
cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be …

Single-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to
technical factors, including the number of molecules detected in each cell, which can …

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

Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …