Construct and Compare scGRN from Single-Cell Transcriptomic Data R package scTenifoldNet version 1.3 CRAN Task View: Omics (https://CRAN.R-project.org/view=Omics) A workflow based on machine learning methods to construct and compare single-cell gene regulatory networks (scGRN) using single-cell RNA-seq (scRNA-seq) data collected from different conditions. Uses principal component regression, tensor decomposition, and manifold alignment, to accurately identify even subtly shifted gene expression programs. See <doi:10.1016/j.patter.2020.100139> for more details. Software Imports: pbapply, RSpectra, Matrix, methods, stats, utils, MASS, RhpcBLASctl Suggests: testthat (>= 2.1.0) Daniel Osorio <dcosorioh@utexas.edu> Comprehensive R Archive Network (CRAN) Daniel Osorio [aut, cre] (ORCID: <https://orcid.org/0000-0003-4424-8422>), Yan Zhong [aut, ctb], Guanxun Li [aut, ctb], Jianhua Huang [aut, ctb], James Cai [aut, ctb, ths] (ORCID: <https://orcid.org/0000-0002-8081-6725>) GPL (>= 2) 2021-10-29 application/tgz https://CRAN.R-project.org/package=scTenifoldNet doi:10.32614/CRAN.package.scTenifoldNet