Batch-effect correction in single-cell RNA sequencing data using JIVE
In single-cell RNA sequencing (scRNA-seq) data analysis, addressing batch effects – technical artifacts stemming from…
In single-cell RNA sequencing (scRNA-seq) data analysis, addressing batch effects – technical artifacts stemming from…
Identifying cancerous samples or cells using transcriptomic data is critical for cancer related basic research,…
Single-cell RNA-seq (scRNA-seq) analysis of multiple samples separately can be costly and lead to batch…
Single-cell RNA sequencing (scRNA-seq) technology has enabled assessment of transcriptome-wide changes at single-cell resolution. Due…
The accurate estimation of cell surface receptor abundance for single cell transcriptomics data is important…
A team led by researchers at the Ohio State University have developed a novel positive…
Next-generation RNA sequencing (RNA-seq) technology has been widely used to assess full-length RNA isoform abundance…
Single-cell RNA sequencing (scRNA-seq) data has been widely used for cell trajectory inference, with the…
Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells, which has given…
Gene expression is characterised by stochastic bursts of transcription that occur at brief and random…