Single-cell transcriptome analysis overcomes problems inherently associated with
averaging gene expression measurements in bulk analysis. However, single-cell analysis is …

Single-cell transcriptomics reveals gene expression heterogeneity but suffers from
stochastic dropout and characteristic bimodal expression distributions in which expression is …

Single-cell gene expression analyses hold promise for characterizing cellular heterogeneity,
but current methods compromise on either the coverage, the sensitivity or the throughput …

Single-cell technologies have emerged as advanced tools to study various biological
processes that demand the single cell resolution. To detect subtle heterogeneity in the …

Complex biological systems are composed of multiple cell types whose transcriptional
activity can vary due to differences in cell state, environmental stimulation, or intrinsic …

Single-cell gene expression studies promise to reveal rare cell types and cryptic states, but
the high variability of single-cell RNA-seq measurements frustrates efforts to assay …

Single-cell genomics and single-cell transcriptomics have emerged as powerful tools to
study the biology of single cells at a genome-wide scale. However, a major challenge is to …

Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression
heterogeneity in populations of cells. Many techniques have, thus, been recently developed …

Recent technological and algorithmic advances enable single-cell transcriptomic analysis
with remarkable depth and breadth. Nonetheless, a persistent challenge is the compromise …

Interest in single-cell whole-transcriptome analysis is growing rapidly, especially for profiling
rare or heterogeneous populations of cells. We compared commercially available single-cell …