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Updated: Oct 11, 2025
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Published on: January 10, 2019
SCRIP: an accurate simulator for single-cell RNA sequencing data
Fei Qin1, Xizhi Luo1, Feifei Xiao1
1Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA.
Motivation:
Recent advancements in single-cell RNA sequencing (scRNA-seq) have enabled time-efficient transcriptome profiling in individual cells. To optimize sequencing protocols and develop reliable analysis methods for various application scenarios, solid simulation methods for scRNA-seq data are required. However, due to the noisy nature of scRNA-seq data, currently available simulation methods cannot sufficiently capture and simulate important properties of real data, especially the biological variation. In this study, we developed scRNA-seq information producer (SCRIP), a novel simulator for scRNA-seq that is accurate and enables simulation of bursting kinetics.
Results:
Compared to existing simulators, SCRIP showed a significantly higher accuracy of stimulating key data features, including mean-variance dependency in all experiments. SCRIP also outperformed other methods in recovering cell-cell distances. The application of SCRIP in evaluating differential expression analysis methods showed that edgeR outperformed other examined methods in differential expression analyses, and ZINB-WaVE improved the AUC at high dropout rates. Collectively, this study provides the research community with a rigorous tool for scRNA-seq data simulation.
Availability And Implementation:
https://CRAN.R-project.org/package=SCRIP.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
