scTenifoldNet and scTenifoldKnk: A package suite for single-cell gene regulatory network construction, comparison, and perturbation analysis

Yan Zhong, Daniel Osorio, Guanxun Li, Qian Xu, Yongjian Yang, Jianhua Z. Huang and James J. Cai

Statistical Theory and Related Fields, 2025, vol. 9, issue 4, 357-366

Abstract: The comparative analysis of gene regulatory networks (GRNs) across various biological conditions reveals crucial shifts in regulatory mechanisms, shedding light on how genetic and environmental signals influence gene function. Recent advances in highresolution technologies have provided support and made it possible to profile gene expression at the single-cell level, thereby enabling more precise studies of transcriptional regulation. We have developed the scTenifoldNet and scTenifoldKnk R packages, which offer streamlined workflows for constructing single-cell gene regulatory networks (scGRNs) and facilitating comparisons across different samples or between pre- and post-gene perturbation states. Both packages employ a “tensor decomposition + manifold alignment” approach to achieve robust and effective comparisons.

Date: 2025
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DOI: 10.1080/24754269.2025.2557719

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