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 …

Single-cell RNA-seq (scRNASeq) has become a powerful technique for measuring the
transcriptome of individual cells. Unlike the bulk measurements that average the gene …

Elucidation of cell subpopulations at high resolution is a key and challenging goal of single-
cell ribonucleic acid (RNA) sequencing (scRNA-seq) data analysis. Although unsupervised …

Cell clustering is one of the most important and commonly performed tasks in single-cell
RNA sequencing (scRNA-seq) data analysis. An important step in cell clustering is to select …

Motivation Accurately clustering cell types from a mass of heterogeneous cells is a crucial
first step for the analysis of single-cell RNA-seq (scRNA-Seq) data. Although several …

Advances in high-throughput sequencing on single-cell gene expressions [single-cell RNA
sequencing (scRNA-seq)] have enabled transcriptome profiling on individual cells from …

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 …

Single-cell RNA-seq (scRNAseq) is a powerful tool to study heterogeneity of cells. Recently,
several clustering based methods have been proposed to identify distinct cell populations …

Background Single-cell RNA-sequencing (scRNA-seq) is a transformative technology,
allowing global transcriptomes of individual cells to be profiled with high accuracy. An …

Abstract Single-cell RNA-Sequencing (scRNA-Seq) is a revolutionary technique for
discovering and describing cell types in heterogeneous tissues, yet its measurement of …