A shiny application for single cell RNA-seq visualization
Author(s): Jianhong Ou
Affiliation(s): Duke Regeneration Center, Duke University
Social media: https://twitter.com/gaziou
Single-cell RNA sequencing (scRNA-seq) is a powerful technique to study gene expression, cellular heterogeneity, and cell states within samples in single-cell level. The development of scRNA-seq shed light to address the knowledge gap about the cell types, cell interactions, and key genes involved in biological process and their dynamics. To precisely meet the publishing requirement, reduce the time of communication the bioinformatician with researchers, and increase the re-usability and reproducibility of scientific findings, multiple interactive visualization tools were developed to provide the researchers access to the details of the data. Based on ShinyCell, the scRNAseqApp package is developed with multiple highly interactive visualizations of how cells and subsets of cells cluster behavior for scRNA-seq, scATAC-seq and sc-multiomics data. The end users can discover the expression of genes in multiple interactive manners with highly customized filter conditions by selecting metadata supplied with the publications and download the ready-to-use results for republishing.