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scTenifoldNet  

Construct and Compare scGRN from Single-Cell Transcriptomic Data
View on CRAN: Click here


Download and install scTenifoldNet package within the R console
Install from CRAN:
install.packages("scTenifoldNet")

Install from Github:
library("remotes")
install_github("cran/scTenifoldNet")

Install by package version:
library("remotes")
install_version("scTenifoldNet", "1.3")



Attach the package and use:
library("scTenifoldNet")
Maintained by
Daniel Osorio
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-15
Latest Update: 2021-10-29
Description:
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 for more details.
How to cite:
Daniel Osorio (2019). scTenifoldNet: Construct and Compare scGRN from Single-Cell Transcriptomic Data. R package version 1.3, https://cran.r-project.org/web/packages/scTenifoldNet. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0.0 (2019-12-15 15:30), 1.1.0 (2020-01-08 20:50), 1.2.0 (2020-03-10 19:00), 1.2.1 (2020-04-09 11:10), 1.2.2 (2020-05-13 22:40), 1.2.3 (2020-08-26 00:20), 1.2.4 (2020-11-17 09:20)
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Complete documentation for scTenifoldNet
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