Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
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DOI：
10.15302/j-qb-022-0299
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发表时间：
2022-12
期刊：
影响因子：
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通讯作者：
Yueshan Zhao;M. Zhang;D. Yang
中科院分区：
文献类型：
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作者：
Yueshan Zhao;M. Zhang;D. Yang
背景：利用CRISPR基因敲除(CRISPRko)、CRISPR干扰(CRISPRi)和CRISPR激活(CRISPRa)三种不同的系统，联合CRISPR筛选是一种很有前途的药物靶点或必需基因鉴定工具。除了技术的不断进步外，越来越多的生物信息学方法被开发出来用于分析CRISPR屏幕获得的数据，这有助于更好地了解生理效应。结果：在这里，我们提供了CRISPR筛查和生物信息学方法在分析不同类型CRISPR筛查数据方面的应用概述。我们还讨论了分析辍学筛选、基于排序的筛选和单细胞筛选的机制和潜在挑战。结论：应根据屏幕的设计选择不同的分析方法。这篇综述将帮助社区更好地设计新的算法，并为湿实验室研究人员提供建议，以从不同的分析方法中进行选择。
Background: Pooled CRISPR screen is a promising tool in drug targets or essential genes identification with the utilization of three different systems including CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa). Aside from continuous improvements in technology, more and more bioinformatics methods have been developed to analyze the data obtained by CRISPR screens which facilitate better understanding of physiological effects. Results: Here, we provide an overview on the application of CRISPR screens and bioinformatics approaches to analyzing different types of CRISPR screen data. We also discuss mechanisms and underlying challenges for the analysis of dropout screens, sorting-based screens and single-cell screens. Conclusion: Different analysis approaches should be chosen based on the design of screens. This review will help community to better design novel algorithms and provide suggestions for wet-lab researchers to choose from different analysis methods.