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Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets [10X]

ABSTRACT: Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets [10X]

PROVIDER: PRJNA597064 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10751500.fastq.gz	Fastqsanger.gz
	SRR10751501.fastq.gz	Fastqsanger.gz
	SRR10751502.fastq.gz	Fastqsanger.gz
	SRR10751503.fastq.gz	Fastqsanger.gz
	SRR10751504.fastq.gz	Fastqsanger.gz

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Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets [10X]

Project description:Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy beyond those achievable with current methods for qualitative single cell characterization. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses. We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and show that the ensuing biases can effectively be removed by a novel bioinformatics method. Applying this method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples. This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells allows to clarify the complexities of the cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy.

2020-03-19 | GSE142465 | GEO

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets

Project description:Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets

| PRJNA613399 | ENA

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets [Drop-seq]

Project description:Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets [Drop-seq]

| PRJNA613402 | ENA

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets.

Project description:BACKGROUND:Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy-beyond those achievable with existing methods for mainly qualitative single-cell analysis. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses. RESULTS:We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and we show that the ensuing biases can be removed effectively using a novel bioinformatics algorithm. Applying our method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples. CONCLUSIONS:This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells helps clarify complex cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy.

| S-EPMC7201533 | biostudies-literature

Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

Project description:We designed spike-in controls for cfMeDIP-seq experiments. These spike-in controls mitigate batch effects and allow for absolute quantification of cell-free DNA.

| EGAS00001005069 | EGA

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-03-19 | GSE147203 | GEO

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale [III]

Project description:Analysis of allele-specific expression is strongly affected by the technical noise present in RNA-seq experiments. Previously, we showed that technical replicates can be used for precise estimates of this noise, and we provided a tool for correction of technical noise in allele-specific expression analysis. This approach is very accurate but costly due to the need for two or more replicates of each library. Here, we develop a spike-in approach that is highly accurate at only a small fraction of the cost. We show that a distinct RNA added as a spike-in before library preparation reflects technical noise of the whole library and can be used in large batches of samples. We experimentally demonstrate the effectiveness of this approach using combinations of RNA from species distinguishable by alignment, namely, mouse, human, and C.elegans. Our new approach, controlFreq, enables highly accurate and computationally efficient analysis of allele-specific expression in (and between) arbitrarily large studies at an overall cost increase of ∼ 5%.

2023-07-11 | GSE228004 | GEO

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale [II]

2023-07-11 | GSE228003 | GEO

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale [I]

2023-07-11 | GSE228002 | GEO

Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets [Drop-seq]

Project description:Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. Here we treated human islet ex vivo with drugs to study the changes in their cellular identity. Artemether treatment upregulated insulin and other beta cell marker genes in a subset of alpha cells.

2020-03-20 | GSE147202 | GEO

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