Package: scTenifoldNet 1.3

Daniel Osorio

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.

Authors:Daniel Osorio [aut, cre], Yan Zhong [aut, ctb], Guanxun Li [aut, ctb], Jianhua Huang [aut, ctb], James Cai [aut, ctb, ths]

scTenifoldNet_1.3.tar.gz
scTenifoldNet_1.3.zip(r-4.5)scTenifoldNet_1.3.zip(r-4.4)scTenifoldNet_1.3.zip(r-4.3)
scTenifoldNet_1.3.tgz(r-4.4-any)scTenifoldNet_1.3.tgz(r-4.3-any)
scTenifoldNet_1.3.tar.gz(r-4.5-noble)scTenifoldNet_1.3.tar.gz(r-4.4-noble)
scTenifoldNet_1.3.tgz(r-4.4-emscripten)scTenifoldNet_1.3.tgz(r-4.3-emscripten)
scTenifoldNet.pdf |scTenifoldNet.html✨
scTenifoldNet/json (API)

Peer review:

Bug tracker:https://github.com/cailab-tamu/sctenifoldnet/issues

On CRAN:

differential-regulation-analysisgene-regulatory-networksmanifold-alignmentsingle-celltensor-decomposition

8 exports 21 stars 2.28 score 8 dependencies 1 dependents 73 scripts 352 downloads

Last updated 2 years agofrom:de53dc2b2f. Checks:OK: 7. Indexed: yes.

Exports:cpmNormalizationdRegulationmakeNetworksmanifoldAlignmentpcNetscQCscTenifoldNettensorDecomposition

Dependencies:latticeMASSMatrixpbapplyRcppRcppEigenRhpcBLASctlRSpectra