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scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens

We present scMAGeCK, a computational framework to identify genomic elements associated with multiple expression-based phenotypes in CRISPR/Cas9 functional screening that uses single-cell RNA-seq as readout. scMAGeCK outperforms existing methods, identifies genes and enhancers with known and novel fu...

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Detalles Bibliográficos
Autores principales: Yang, Lin, Zhu, Yuqing, Yu, Hua, Cheng, Xiaolong, Chen, Sitong, Chu, Yulan, Huang, He, Zhang, Jin, Li, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979386/
https://www.ncbi.nlm.nih.gov/pubmed/31980032
http://dx.doi.org/10.1186/s13059-020-1928-4
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author Yang, Lin
Zhu, Yuqing
Yu, Hua
Cheng, Xiaolong
Chen, Sitong
Chu, Yulan
Huang, He
Zhang, Jin
Li, Wei
author_facet Yang, Lin
Zhu, Yuqing
Yu, Hua
Cheng, Xiaolong
Chen, Sitong
Chu, Yulan
Huang, He
Zhang, Jin
Li, Wei
author_sort Yang, Lin
collection PubMed
description We present scMAGeCK, a computational framework to identify genomic elements associated with multiple expression-based phenotypes in CRISPR/Cas9 functional screening that uses single-cell RNA-seq as readout. scMAGeCK outperforms existing methods, identifies genes and enhancers with known and novel functions in cell proliferation, and enables an unbiased construction of genotype-phenotype network. Single-cell CRISPR screening on mouse embryonic stem cells identifies key genes associated with different pluripotency states. Applying scMAGeCK on multiple datasets, we identify key factors that improve the power of single-cell CRISPR screening. Collectively, scMAGeCK is a novel tool to study genotype-phenotype relationships at a single-cell level. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-020-1928-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-69793862020-01-29 scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens Yang, Lin Zhu, Yuqing Yu, Hua Cheng, Xiaolong Chen, Sitong Chu, Yulan Huang, He Zhang, Jin Li, Wei Genome Biol Method We present scMAGeCK, a computational framework to identify genomic elements associated with multiple expression-based phenotypes in CRISPR/Cas9 functional screening that uses single-cell RNA-seq as readout. scMAGeCK outperforms existing methods, identifies genes and enhancers with known and novel functions in cell proliferation, and enables an unbiased construction of genotype-phenotype network. Single-cell CRISPR screening on mouse embryonic stem cells identifies key genes associated with different pluripotency states. Applying scMAGeCK on multiple datasets, we identify key factors that improve the power of single-cell CRISPR screening. Collectively, scMAGeCK is a novel tool to study genotype-phenotype relationships at a single-cell level. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-020-1928-4) contains supplementary material, which is available to authorized users. BioMed Central 2020-01-24 /pmc/articles/PMC6979386/ /pubmed/31980032 http://dx.doi.org/10.1186/s13059-020-1928-4 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Yang, Lin
Zhu, Yuqing
Yu, Hua
Cheng, Xiaolong
Chen, Sitong
Chu, Yulan
Huang, He
Zhang, Jin
Li, Wei
scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
title scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
title_full scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
title_fullStr scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
title_full_unstemmed scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
title_short scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens
title_sort scmageck links genotypes with multiple phenotypes in single-cell crispr screens
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979386/
https://www.ncbi.nlm.nih.gov/pubmed/31980032
http://dx.doi.org/10.1186/s13059-020-1928-4
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