Garvan Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, Darlinghurst, NSW, 2010, Australia.
UNSW Cellular Genomics Futures Institute, University of New South Wales, Sydney, NSW, 2052, Australia.
Genome Biol. 2021 Dec 2;22(1):329. doi: 10.1186/s13059-021-02547-0.
Advances in droplet-based single-cell RNA-sequencing (scRNA-seq) have dramatically increased throughput, allowing tens of thousands of cells to be routinely sequenced in a single experiment. In addition to cells, droplets capture cell-free "ambient" RNA predominantly caused by lysis of cells during sample preparation. Samples with high ambient RNA concentration can create challenges in accurately distinguishing cell-containing droplets and droplets containing ambient RNA. Current methods to separate these groups often retain a significant number of droplets that do not contain cells or empty droplets. Additionally, there are currently no methods available to detect droplets containing damaged cells, which comprise partially lysed cells, the original source of the ambient RNA.
Here, we describe DropletQC, a new method that is able to detect empty droplets, damaged, and intact cells, and accurately distinguish them from one another. This approach is based on a novel quality control metric, the nuclear fraction, which quantifies for each droplet the fraction of RNA originating from unspliced, nuclear pre-mRNA. We demonstrate how DropletQC provides a powerful extension to existing computational methods for identifying empty droplets such as EmptyDrops.
We implement DropletQC as an R package, which can be easily integrated into existing single-cell analysis workflows.
基于液滴的单细胞 RNA 测序（scRNA-seq）技术的进步极大地提高了通量，使得在单个实验中可以常规地对数万种细胞进行测序。除了细胞之外，液滴还捕获了主要由样品制备过程中细胞裂解引起的细胞游离的“环境”RNA。高浓度环境 RNA 的样品在准确区分含有细胞的液滴和含有环境 RNA 的液滴方面会带来挑战。目前用于分离这些群体的方法通常保留了大量不含细胞或空液滴的液滴。此外，目前还没有方法可用于检测含有受损细胞的液滴，而这些受损细胞是环境 RNA 的原始来源，包含部分裂解的细胞。
在这里，我们描述了一种新的方法 DropletQC，该方法能够检测空液滴、受损细胞和完整细胞，并能够准确地区分它们。该方法基于一种新的质量控制指标——核分数，它定量地计算了每个液滴中源自未剪接的、核前体 RNA 的 RNA 分数。我们证明了 DropletQC 如何为识别空液滴的现有计算方法（如 EmptyDrops）提供了强大的扩展。
我们将 DropletQC 实现为一个 R 包，可轻松集成到现有的单细胞分析工作流程中。
