The development of high-throughput RNA sequencing (RNA-seq) at the single-cell level has
already led to profound new discoveries in biology, ranging from the identification of novel …

Despite the growing availability of sophisticated bioinformatic methods for the analysis of
single-cell RNA-seq data, few tools exist that allow biologists without extensive bioinformatic …

Differential gene expression analysis is one of the significant efforts in single cell RNA
sequencing (scRNAseq) analysis to discover the specific changes in expression levels of …

The development of high-throughput single-cell RNA sequencing (scRNA-seq) has enabled
access to information about gene expression in individual cells and insights into new …

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in
different laboratories and at different times contain batch effects that may compromise the …

Single-cell RNAsequencing (scRNA-seq) technologies have enabled the large-scale whole-
transcriptome profiling of each individual single cell in a cell population. A core analysis of …

ABSTRACT A multitude of single-cell RNA sequencing methods have been developed in
recent years, with dramatic advances in scale and power, and enabling major discoveries …

The sequencing of the transcriptome of single cells, or single-cell RNA-sequencing, has now
become the dominant technology for the identification of novel cell types in heterogeneous …

The recent developments in high‐throughput single‐cell RNA sequencing technology (sc
RNA‐seq) have enabled the generation of vast amounts of transcriptomic data at cellular …

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 …