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 |
| 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 |
| Reference manual: | scTenifoldNet.html , scTenifoldNet.pdf |
| 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 imports: | scPOEM, scTenifoldKnk |
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