Recent advances in single-cell RNA sequencing technologies have made detection of transcripts in single cells possible. The level of resolution provided by these technologies can be used to study changes in transcript usage across cell populations and help investigate new biology. Researchers from the Michael Smith Genome Sciences Centre, have developed RNA-Scoop, an interactive cell cluster and transcriptome visualization tool to analyze transcript usage across cell categories and clusters. The tool allows users to examine differential transcript expression across clusters and investigate how usage of specific transcript expression mechanisms varies across cell groups.
RNA-Scoop visualization of Clta isoform expression across nine
cell category labels from the ScNaUmi-seq dataset
The transcript view on the left shows the isoform structures of selected genes and its integrated dot plot shows the proportion and magnitude of transcript expression in each cell category. Transcripts and dots are colored according to their non-zero median expression levels in all cells and cells of their particular category, respectively. Dots are not drawn for transcripts not expressed in any cells of a given category. The cell cluster plot on the right shows the clustering of cells based on transcript expression.
Availability – The source and compiled Java archive of RNA-Scoop are available at https://github.com/bcgsc/RNA-Scoop