The identification of differentially expressed genes between different cell groups is a crucial
step in analyzing single-cell RNA-sequencing (scRNA-seq) data. Even though various …

Differential expression (DE) analysis between cell types for scRNA-seq data by capturing its
complicated features is crucial. Recently, different methods have been developed for …

Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput sequencing
technique for studying gene expressions at the cell level. Differential Expression (DE) …

Background The analysis of single-cell RNA sequencing (scRNAseq) data plays an
important role in understanding the intrinsic and extrinsic cellular processes in biological …

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that is capable of
generating gene expression data at the resolution of individual cell. The scRNA-seq data is …

Detection of differentially expressed genes is a common task in single-cell RNA-seq (scRNA-
seq) studies. Various methods based on both bulk-cell and single-cell approaches are in …

Background As single-cell RNA-seq (scRNA-seq) is becoming increasingly common, the
amount of publicly available data grows rapidly, generating a useful resource for …

Differential expression (DE) gene detection in single-cell ribonucleic acid (RNA)-sequencing
(scRNA-seq) data is a key step to understand the biological question investigated. Filtering …

Differential expression (DE) analysis and gene set enrichment (GSE) analysis are commonly
applied in single cell RNA sequencing (scRNA-seq) studies. Here, we develop an …

Motivation Single-cell RNA sequencing (scRNA-seq) has enabled the simultaneous
transcriptomic profiling of individual cells under different biological conditions. scRNA-seq …