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Analisi di RNA-seq a singola cellula basata su network×Analisi eQTL a Singola Cellula×
CampoBioinformaticaBioinformatica
FamigliaProcess / pipelineProcess / pipeline
Anno di origine2015–2017 (rapid development alongside scRNA-seq methods; SCENIC 2017)2020
IdeatoreAibar et al. (SCENIC, gene regulatory networks); Jin et al. (CellChat, cell-cell communication networks)Cuomo et al.; Kim-Hellmuth et al. (pioneering sc-eQTL frameworks, 2020)
TipoComputational bioinformatics pipelineStatistical genomics pipeline
Fonte seminaleAibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., ... & Aerts, S. (2017). SCENIC: single-cell regulatory network inference and clustering. Nature Methods, 14(11), 1083–1086. link ↗Cuomo, A. S. E., et al. (2020). Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression. Nature Communications, 11(1), 810. link ↗
AliasscRNA-seq network analysis, single-cell gene regulatory network inference, scGRN analysis, single-cell co-expression network analysissc-eQTL analysis, single-cell eQTL mapping, scRNA-seq eQTL, cell-type-specific eQTL
Correlati66
SintesiNetwork-based single-cell RNA-seq analysis extends standard scRNA-seq workflows by constructing and interrogating molecular interaction networks — gene regulatory networks, co-expression networks, or cell-cell communication graphs — from single-cell transcriptomic data. Rather than treating each gene independently, this approach captures the coordinated activity of gene circuits and intercellular signalling pathways within and between cell populations, enabling a systems-level view of transcriptional regulation at single-cell resolution.Single-cell eQTL analysis identifies genetic variants (eQTLs) that regulate gene expression in a cell-type-specific manner by jointly analysing single-cell RNA-seq profiles and donor genotype data. Unlike bulk eQTL methods, it resolves regulatory effects that are diluted or masked when cell types are mixed, enabling discovery of variants whose effects are confined to particular cell states or developmental stages.
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ScholarGateConfronta i metodi: Network-based single-cell RNA-seq analysis · Single-cell eQTL analysis. Consultato il 2026-06-17 da https://scholargate.app/it/compare