Original paper
EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data
Abstract
Droplet-based single-cell RNA sequencing protocols have dramatically increased the throughput of single-cell transcriptomics studies. A key computational challenge when processing these data is to distinguish libraries for real cells from empty droplets. Here, we describe a new statistical method for calling cells from droplet-based data, based on detecting significant deviations from the expression profile of the ambient solution. Using...
Paper Details
Title
EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data
Published Date
Mar 22, 2019
Journal
Volume
20
Issue
1