Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhao, Yueshan, Zhang, Min, Yang, Da
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019185/
https://www.ncbi.nlm.nih.gov/pubmed/36937794
_version_ 1784907974201835520
author Zhao, Yueshan
Zhang, Min
Yang, Da
author_facet Zhao, Yueshan
Zhang, Min
Yang, Da
author_sort Zhao, Yueshan
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10019185
institution National Center for Biotechnology Information
language English
publishDate 2022
record_format MEDLINE/PubMed
spelling pubmed-100191852023-03-16 Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens Zhao, Yueshan Zhang, Min Yang, Da Quant Biol Article 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. 2022-12 /pmc/articles/PMC10019185/ /pubmed/36937794 Text en https://creativecommons.org/licenses/by/4.0/OPEN ACCESS: This article is licensed by the CC By under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhao, Yueshan
Zhang, Min
Yang, Da
Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
title Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
title_full Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
title_fullStr Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
title_full_unstemmed Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
title_short Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens
title_sort bioinformatics approaches to analyzing crispr screen data: from dropout screens to single-cell crispr screens
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019185/
https://www.ncbi.nlm.nih.gov/pubmed/36937794
work_keys_str_mv AT zhaoyueshan bioinformaticsapproachestoanalyzingcrisprscreendatafromdropoutscreenstosinglecellcrisprscreens
AT zhangmin bioinformaticsapproachestoanalyzingcrisprscreendatafromdropoutscreenstosinglecellcrisprscreens
AT yangda bioinformaticsapproachestoanalyzingcrisprscreendatafromdropoutscreenstosinglecellcrisprscreens