cailab-tamu/PCrTdMa: 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.

install.packages("remotes")
remotes::install_github("cailab-tamu/PCrTdMa")