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scTenifoldNet: Construct and Compare scGRN from Single-Cell Transcriptomic Data

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.

Version: 1.3
Imports: pbapply, RSpectra, Matrix, methods, stats, utils, MASS, RhpcBLASctl
Suggests: testthat (≥ 2.1.0)
Published: 2021-10-29
DOI: 10.32614/CRAN.package.scTenifoldNet
Author: Daniel Osorio ORCID iD [aut, cre], Yan Zhong [aut, ctb], Guanxun Li [aut, ctb], Jianhua Huang [aut, ctb], James Cai ORCID iD [aut, ctb, ths]
Maintainer: Daniel Osorio <dcosorioh at utexas.edu>
BugReports: https://github.com/cailab-tamu/scTenifoldNet/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/cailab-tamu/scTenifoldNet
NeedsCompilation: no
Citation: scTenifoldNet citation info
Materials: README
In views: Omics
CRAN checks: scTenifoldNet results

Documentation:

Reference manual: scTenifoldNet.pdf

Downloads:

Package source: scTenifoldNet_1.3.tar.gz
Windows binaries: r-devel: scTenifoldNet_1.3.zip, r-release: scTenifoldNet_1.3.zip, r-oldrel: scTenifoldNet_1.3.zip
macOS binaries: r-release (arm64): scTenifoldNet_1.3.tgz, r-oldrel (arm64): scTenifoldNet_1.3.tgz, r-release (x86_64): scTenifoldNet_1.3.tgz, r-oldrel (x86_64): scTenifoldNet_1.3.tgz
Old sources: scTenifoldNet archive

Reverse dependencies:

Reverse imports: scTenifoldKnk

Linking:

Please use the canonical form https://CRAN.R-project.org/package=scTenifoldNet to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.