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

作　　者：Yueshan Zhao Min Zhang Da Yang 

机构地区：[1]Center for Pharmacogenetics,Department of Pharmaceutical Sciences,University of Pittsburgh,Pittsburgh PA 15261,USA [2]UPMC Hillman Cancer Institute,University of Pittsburgh,Pittsburgh,PA 15261,USA [3]Department of Computational and Systems Biology,University of Pittsburgh,Pittsburgh,PA 15261,USA

出　　处：《Quantitative Biology》2022年第4期307-320,共14页定量生物学（英文版）

基　　金：This study was supported by the Shear Family Foundation(to D.Y.),the American Cancer Society Research Scholar Award(132632-RSG-18-179-01-RMC to D.Y.);National Cancer Institute(1R01CA222274 and R01CA255196 to D.Y.).

摘　　要：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.

关 键 词：CRISPR/Cas9 dropout screen sorting-based screen single-cell CRISPR screen drug-gene interaction 

分 类 号：Q78[生物学—分子生物学]