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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
Descripción
Sumario: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.