A novel approach to analyzing single-cell RNA sequencing (scRNA-seq) data has been unveiled by researchers. This method promises to enhance both the precision and speed of data interpretation, ...

Cell clustering can vary wildly depending on algorithm settings like the random seed — even with the exact same data. scICE automatically detects and removes unstable groupings, giving researchers ...

Cell clustering serves as a key task in transcriptomic data analysis, playing a crucial role in cell type annotation, marker gene identification, and the discovery of rare cell populations. With the ...

This study presents a valuable tool named TSvelo, a computational framework for RNA velocity inference that models transcriptional regulation and gene-specific splicing. The evidence supporting the ...