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SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators

ABSTRACT: SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators

PROVIDER: PRJNA722248 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR14243915_1.fastq.gz	Fastqsanger.gz
	SRR14243915_2.fastq.gz	Fastqsanger.gz
	SRR14243916_1.fastq.gz	Fastqsanger.gz
	SRR14243916_2.fastq.gz	Fastqsanger.gz
	SRR14243917_1.fastq.gz	Fastqsanger.gz

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SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators

Project description:The identity and functions of specialized cell types are dependent on the complex interplay between signaling and transcriptional networks. Recently single-cell technologies such as CITE-seq have been developed that enable simultaneous quantitative analysis of cell-surface receptor expression with transcriptional states. To date, these datasets have not been used to systematically develop cell-context-specific maps of the interface between signaling and transcriptional regulators orchestrating cellular identity and function. We present SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network), a computational method to link cell-surface receptors to transcription factors (TFs) by exploiting cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) datasets with cis-regulatory information. SPaRTAN is applied to immune cell types in the blood to predict the coupling of signaling receptors with cell context-specific TFs. The predictions are validated by prior knowledge and flow cytometry analyses. SPaRTAN is then used to predict the signaling coupled TF states of tumor infiltrating CD8+ T cells in malignant peritoneal and pleural mesotheliomas. SPaRTAN greatly enhances the utility of CITE-seq datasets to uncover TF and cell-surface receptor relationships in diverse cellular states.

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SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators.

Project description:The identity and functions of specialized cell types are dependent on the complex interplay between signaling and transcriptional networks. Recently single-cell technologies have been developed that enable simultaneous quantitative analysis of cell-surface receptor expression with transcriptional states. To date, these datasets have not been used to systematically develop cell-context-specific maps of the interface between signaling and transcriptional regulators orchestrating cellular identity and function. We present SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network), a computational method to link cell-surface receptors to transcription factors (TFs) by exploiting cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) datasets with cis-regulatory information. SPaRTAN is applied to immune cell types in the blood to predict the coupling of signaling receptors with cell context-specific TFs. Selected predictions are validated by prior knowledge and flow cytometry analyses. SPaRTAN is then used to predict the signaling coupled TF states of tumor infiltrating CD8+ T cells in malignant peritoneal and pleural mesotheliomas. SPaRTAN enhances the utility of CITE-seq datasets to uncover TF and cell-surface receptor relationships in diverse cellular states.

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Computational and Analytical Framework for Small RNA Profiling by High-Throughput Sequencing

Project description:This SuperSeries is composed of the following subset Series: GSE14694: Computational and Analytical Framework for Small RNA Profiling by High-Throughput Sequencing (reproducibility) GSE14695: Computational and Analytical Framework for Small RNA Profiling by High-Throughput Sequencing (standards) Refer to individual Series

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Identification of transcription factors dictating blood cell development using a bidirectional transcription network-based computational framework [CAGEseq_THP1_GSK-LSD1]

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