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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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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. |
format | Online Article Text |
id | pubmed-6979386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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