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bioRxiv · 10.1101/2023.01.31.526445

scDecouple: Decoupling cellular response and infection bias in scCRISPR-seq

Meng, Q.·Shi, M.·Wei, L.·Li, Y.·Zhang, X.
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Abstract

MotivationscCRISPR-seq is an emerging high-throughput CRISPR screening technology that combines CRISPR screening with single-cell sequencing technologies. It provides rich information on the mechanism of gene regulation. However, when scCRISPR-seq is applied in a population of heterogeneous cells, the true cellular response to perturbation is coupled with infected proportion bias of guide RNAs (gRNAs) across different cell clusters. The mixing of these effects introduces noise into scCRISPR-seq data analysis and thus obstacles to relevant studies. ResultsWe developed scDecouple to decouple true cellular response of perturbation from the influence of infected proportion bias. scDecouple first models the distribution of gene expression profiles in perturbed cells and then iteratively finds the maximum likelihood of cell cluster proportions as well as the cellular response for each gRNA. We demonstrated its performance in a series of simulation experiments. By applying scDecouple to real scCRISPR-seq data, we found that scDecouple enhances the identification of biologically perturbation-related genes. scDecouple can benefit scCRISPR-seq data analysis, especially in the case of heterogeneous samples or complex gRNA libraries. AvailabilityscDecouple is freely available at https://github.com/MengQiuchen/scDecouple. Contactweilei92@tsinghua.edu.cn, yinqingl@tsinghua.edu.cn

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Meng, Q., Shi, M., Wei, L., Li, Y., Zhang, X.. 2023-02-03. scDecouple: Decoupling cellular response and infection bias in scCRISPR-seq. https://doi.org/10.1101/2023.01.31.526445

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