We present SCORPION, a computational tool to model gene regulatory networks based on single-cell transcriptomic data and prior knowledge of gene regulation. SCORPION networks can be modeled for specific cell types in individual samples, and are therefore suitable for conducting comparisons between experimental groups.
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References
Bilous, M. et al. Metacells untangle large and complex single-cell transcriptome networks. BMC Bioinform. 23, 336 (2022). A paper that presents the methodology used by SCORPION to desparsify the single-cell RNA-seq data used as input.
Glass, K. et al. Passing messages between biological networks to refine predicted interactions. PLoS One 8, e64832 (2013). This paper reports the PANDA algorithm used by SCORPION to integrate the information from single-cell RNA-seq and prior information on protein–protein interaction and TF–gene associations.
Pratapa, A. et al. Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data. Nat Methods. 17, 147–154 (2020). This paper presents a standardized methodology to test the performance of methods for the construction of a gene regulatory network from single-cell RNA-seq data.
Chen, L. et al. A reinforcing HNF4-SMAD4 feed-forward module stabilizes enterocyte identity. Nat Genet. 51, 777–785 (2019). This paper presents an experimental double knockout experiment used as input to validate the performance of SCORPION.
Taubenschmid-Stowers, J. et al. 8C-like cells capture the human zygotic genome activation program in vitro. Cell Stem Cell 29, 449–459 (2022). This article reports an experimental transcription factor over-expression experiment used as input to validate the performance of SCORPION.
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This is a summary of: Osorio, D. et al. Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data. Nat. Comput. Sci. https://doi.org/10.1038/s43588-024-00597-5 (2024).
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Enabling comparative gene regulatory network analysis on single-cell data with SCORPION. Nat Comput Sci 4, 167–168 (2024). https://doi.org/10.1038/s43588-024-00615-6
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DOI: https://doi.org/10.1038/s43588-024-00615-6
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