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scTenifoldNet: Construct and Compare scGRN from Single-Cell Transcriptomic Data
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@dosorio dosorio released this 09 Apr 13:56
v1.2.0
c9cf8f5

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.

  • rTensor dependency was removed
  • Li, J., Bien, J., & Wells, M. T. (2018). rTensor: An R Package for Multidimensional Array (Tensor) Unfolding, Multiplication, and Decomposition. Journal of Statistical Software, 87(10), 1-31. Citation was added
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