Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens.

Pub Date : 2022-12-01
Yueshan Zhao, Min Zhang, Da Yang
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Abstract

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.

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分析CRISPR筛选数据的生物信息学方法:从辍学筛选到单细胞CRISPR筛选。
背景:利用CRISPR敲除(CRISPRko)、CRISPR干扰(CRISPRi)和CRISPR激活(CRISPRa)三种不同的系统,汇集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筛选获得的数据,从而更好地了解生理效应。在这里,我们概述了CRISPR筛选和生物信息学方法在分析不同类型CRISPR筛选数据中的应用。我们还讨论了机制和潜在的挑战,以分析辍学筛选,基于分选的筛选和单细胞筛选。结论:应根据筛选设计选择不同的分析方法。这一综述将有助于更好地设计新的算法,并为湿实验室研究人员从不同的分析方法中选择提供建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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