Zhao Yueshan, Zhang Min, Yang Da
Center for Pharmacogenetics, Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh PA 15261, USA.
UPMC Hillman Cancer Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Quant Biol. 2022 Dec;10(4):307-320.
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.
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.
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.
汇集式CRISPR筛选是一种很有前景的工具，可利用包括CRISPR敲除（CRISPRko）、CRISPR干扰（CRISPRi）和CRISPR激活（CRISPRa）在内的三种不同系统来鉴定药物靶点或必需基因。除了技术上的不断改进，越来越多的生物信息学方法被开发出来，用于分析通过CRISPR筛选获得的数据，这有助于更好地理解生理效应。
在此，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。我们还讨论了对缺失筛选、基于分选的筛选和单细胞筛选进行分析的机制及潜在挑战。
应根据筛选设计选择不同的分析方法。本综述将有助于该领域更好地设计新算法，并为湿实验室研究人员从不同分析方法中进行选择提供建议。
