Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization. Issue 2 (24th November 2021)

• Record Type: Journal Article
• Authors: Bacher, Rhonda; Chu, Li-Fang; Argus, Cara; Bolin, Jennifer M; Knight, Parker; Thomson, James A; Stewart, Ron; Kendziorski, Christina
• Is Part Of: Nucleic acids research. Volume 50:Issue 2(2022)
• Page Start: e12
• Page End: e12
• Publication Date: 2021-11-24
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkab1071
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17–31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.