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

Yueshan Zhao, Min Zhang, Da Yang

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Quant. Biol. ›› 2022, Vol. 10 ›› Issue (4) : 307-320. DOI: 10.15302/J-QB-022-0299
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Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens

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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.

Author summary

CRISPR screen has become a promising tool in the identification of essential genes or drug targets. In this review, 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.

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Keywords

CRISPR/Cas9 / dropout screen / sorting-based screen / single-cell CRISPR screen / drug-gene interaction

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Yueshan Zhao, Min Zhang, Da Yang. Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens. Quant. Biol., 2022, 10(4): 307‒320 https://doi.org/10.15302/J-QB-022-0299

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ACKNOWLEDGEMENTS

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.), and National Cancer Institute (1R01CA222274 and R01CA255196 to D.Y.).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Yueshan Zhao, Min Zhang and Da Yang declare that they have no conflict of interests.
This review does not contain any studies with human or animal subjects performed by any of the authors.

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