A rank-based marker selection method for high throughput scRNA-seq data

摘要

In recent years, single cell RNA sequencing (scRNA-seq) has made it possible to characterize cellular diversity by determining detailed gene expression profiles of specific cell types and states ([1, 2]). Furthermore, mRNA data can now be collected from more than one million cells in one experiment due to the development of high throughput microfluidic sequencing protocols [3]. The incorporation of unique molecular identifier (UMI) technology additionally makes it possible to process these raw sequencing data into integer valued read counts (instead of the “counts per million fragments” types of rates that were used in bulk sequencing [1]). Thus, modern scRNA-seq experiments produce massive amounts of integer valued counts data.