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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
  • , James J. Cai
  • *此作品的通讯作者
  • QIAGEN Digital Insights
  • Beijing Normal University
  • Texas A&M University
  • The Chinese University of Hong Kong, Shenzhen

科研成果: 期刊稿件文章同行评审

摘要

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.

源语言英语
页(从-至)357-366
页数10
期刊Statistical Theory and Related Fields
9
4
DOI
出版状态已出版 - 2025

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