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Chen, Kevin; Ozturk, Kivilcim; Liefeld, Ted; Reich, Michael; Mesirov, Jill P.; Carter, Hannah; Fraley, Stephanie I.
STAR protocols, 06/2021, Letnik: 2, Številka: 2Journal Article
Here, we describe a protocol combining functional metrics with genomic data to elucidate drivers of within-cell-type heterogeneity via the phenotype-to-genotype link. This technique involves using fluorescence tagging to label and isolate cells grown in 3D culture, enabling high-throughput enrichment of phenotypically defined cell subpopulations by fluorescence-activated cell sorting. We then perform a validated phenotypically supervised single-cell analysis pipeline to reveal unique functional cell states, including genes and pathways that contribute to cellular heterogeneity and were undetectable by unsupervised analysis. For complete details on the use and execution of this protocol, please refer to Chen et al. (2020). Display omitted •Sorting of cells by the phenotype from 3D culture is achieved through photoconversion•The photolabeling technique is adaptable to other systems, cells, and phenotypes•Phenotypically supervised analysis reveals novel insights into cellular heterogeneity•A GenePattern notebook facilitates phenotypically supervised scRNAseq analysis Here, we describe a protocol combining functional metrics with genomic data to elucidate drivers of within-cell-type heterogeneity via the phenotype-to-genotype link. This technique involves using fluorescence tagging to label and isolate cells grown in 3D culture, enabling high-throughput enrichment of phenotypically defined cell subpopulations by fluorescence-activated cell sorting. We then perform a validated phenotypically supervised single-cell analysis pipeline to reveal unique functional cell states, including genes and pathways that contribute to cellular heterogeneity and were undetectable by unsupervised analysis.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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