r-sctenifoldnet 1.3
Propagated dependencies: r-rspectra@0.16-2 r-rhpcblasctl@0.23-42 r-pbapply@1.7-2 r-matrix@1.7-1 r-mass@7.3-61
Channel: guix-cran
Home page: https://github.com/cailab-tamu/scTenifoldNet
Licenses: GPL 2+
Synopsis: Construct and Compare scGRN from Single-Cell Transcriptomic Data
Description:
This package provides 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.
Total results: 1