Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology
performed at the level of an individual cell, which can have a potential to understand cellular …

Background Dimensionality reduction is an indispensable analytic component for many
areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality …

With recent advances in single-cell RNA sequencing, enormous transcriptome datasets
have been generated. These datasets have furthered our understanding of cellular …

High-dimensional data, such as those generated by single-cell RNA sequencing (scRNA-
seq), present challenges in interpretation and visualization. Numerical and computational …

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the
low-dimensional embeddings estimated in the dimension-reduction step may not be …

Single-cell RNA sequencing (scRNA-seq) is a powerful technique to analyze the
transcriptomic heterogeneities at the single cell level. It is an important step for studying cell …

Background Single cell RNA sequencing (scRNA-seq) is applied to assay the individual
transcriptomes of large numbers of cells. The gene expression at single-cell level provides …

To process large-scale single-cell RNA-sequencing (scRNA-seq) data effectively without
excessive distortion during dimension reduction, we present SHARP, an ensemble random …

Single-cell RNA sequencing (scRNA-seq) is a revolutionary breakthrough that determines
the precise gene expressions on individual cells and deciphers cell heterogeneity and …

Dimensionality reduction is crucial for the visualization and interpretation of the high-
dimensional single-cell RNA sequencing (scRNA-seq) data. However, preserving …