The rapid progress of protocols for sequencing single-cell transcriptomes over the past
decade has been accompanied by equally impressive advances in the computational …

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

Motivation Single-cell RNA sequencing (scRNA-seq) is increasingly used to study gene
expression at the level of individual cells. However, preparing raw sequence data for further …

Many methods have been used to determine differential gene expression from single-cell
RNA (scRNA)-seq data. We evaluated 36 approaches using experimental and synthetic …

Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as
biological signals representing no or low gene expression, while others regard zeros as …

With few exceptions, the marked advances in knowledge about the genetic basis of
schizophrenia have not converged on findings that can be confidently used for precise …

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has
advanced our understanding of the pathogenesis of disease and provided valuable insights …

Cells from the same individual share common genetic and environmental backgrounds and
are not statistically independent; therefore, they are subsamples or pseudoreplicates. Thus …

Background A fundamental fact in biology states that genes do not operate in isolation, and
yet, methods that infer regulatory networks for single cell gene expression data have been …

The excessive amount of zeros in single-cell RNA-seq (scRNA-seq) data includes 'real'zeros
due to the on-off nature of gene transcription in single cells and 'dropout'zeros due to …