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Computational identification of clonal cells in single-cell CRISPR screens

ABSTRACT: Computational identification of clonal cells in single-cell CRISPR screens

PROVIDER: PRJNA771674 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR16355902_1.fastq.gz	Fastqsanger.gz
	SRR16355902_2.fastq.gz	Fastqsanger.gz
	SRR16355903_1.fastq.gz	Fastqsanger.gz
	SRR16355903_2.fastq.gz	Fastqsanger.gz
	SRR16355904_1.fastq.gz	Fastqsanger.gz

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Computational identification of clonal cells in single-cell CRISPR screens

Project description:Single-cell CRISPR screens are powerful tools to understand genome function by linking genetic perturbations to transcriptome-wide phenotypes. However, since few cells can be affordably sequenced in these screens, biased sampling of cells could affect data interpretation. One potential source of biased sampling is clonal cell expansion. Here, we present a computational pipeline for clonal cell identification in single cell screens using multiplexed sgRNA barcodes. We find that the cells in each clone share transcriptional similarities and we infer the segmental copy number changes in clonal cells. These analyses suggest that clones are genetically distinct. Finally, we show that the transcriptional similarities of clonally expanded cells contribute to false positives in single-cell CRISPR screens. As a result, experimental conditions that reduce clonal expansion or computational filtering of clonal cells will improve the reliability of single-cell CRISPR screens.

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Computational identification of clonal cells in single-cell CRISPR screens.

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