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Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming I

ABSTRACT: Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming I

PROVIDER: PRJNA417182 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR6257340.fastq.gz	Fastqsanger.gz
	SRR6257350.fastq.gz	Fastqsanger.gz
	SRR6257341.fastq.gz	Fastqsanger.gz
	SRR6257351.fastq.gz	Fastqsanger.gz
	SRR6257342.fastq.gz	Fastqsanger.gz

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Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming

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Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming

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Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming I

Project description:We collected single or duplicate samples at the various time points, generated single cell suspensions and performed scRNA-Seq. We also collected samples from established iPSC lines reprogrammed from the same MEFs, maintained in either 2i or serum conditions. Overall, we profiled 68,339 cells to an average depth of 38,462 reads per cell. After discarding cells with less than 1,000 genes detected, we retained a total of 65,781 cells, with a median of 2,398 genes and 7,387 unique transcripts per cell.

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Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming III

Project description:We collected triplicate samples at day 15 under serum condition, generated single cell suspensions and performed scRNA-Seq (10X Genomics). We also collected samples from a bulk population and performed bulk RNA-seq (Quantseq, Lexogen).

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