Package: scTenifoldKnk 1.0.2

Daniel Osorio

scTenifoldKnk: In-Silico Knockout Experiments from Single-Cell Gene Regulatory Networks

A workflow based on 'scTenifoldNet' to perform in-silico knockout experiments using single-cell RNA sequencing (scRNA-seq) data from wild-type (WT) control samples as input. First, the package constructs a single-cell gene regulatory network (scGRN) and knocks out a target gene from the adjacency matrix of the WT scGRN by setting the gene’s outdegree edges to zero. Then, it compares the knocked out scGRN with the WT scGRN to identify differentially regulated genes, called virtual-knockout perturbed genes, which are used to assess the impact of the gene knockout and reveal the gene’s function in the analyzed cells.

Authors:Daniel Osorio [aut, cre], Yan Zhong [aut, ctb], Guanxun Li [aut, ctb], Qian Xu [aut, ctb], Andrew Hillhouse [aut, ctb], Jingshu Chen [aut, ctb], Laurie Davidson [aut, ctb], Yanan Tian [aut, ctb], Robert Chapkin [aut, ctb], Jianhua Huang [aut, ctb], James Cai [aut, ctb, ths]

scTenifoldKnk_1.0.2.tar.gz
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scTenifoldKnk_1.0.2.tgz(r-4.4-any)scTenifoldKnk_1.0.2.tgz(r-4.3-any)
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scTenifoldKnk.pdf |scTenifoldKnk.html
scTenifoldKnk/json (API)

# Install 'scTenifoldKnk' in R:
install.packages('scTenifoldKnk', repos = c('https://cailab-tamu.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

On CRAN:

functional-genomicsgene-functiongene-knockoutgene-regulatory-networkvirtual-knockout-experiments

1 exports 36 stars 2.74 score 9 dependencies 10 scripts 159 downloads

Last updated 2 years agofrom:a15ea4806b. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winNOTESep 13 2024
R-4.5-linuxNOTESep 13 2024
R-4.4-winNOTESep 13 2024
R-4.4-macNOTESep 13 2024
R-4.3-winNOTESep 13 2024
R-4.3-macNOTESep 13 2024

Exports:scTenifoldKnk

Dependencies:latticeMASSMatrixpbapplyRcppRcppEigenRhpcBLASctlRSpectrascTenifoldNet

Readme and manuals

Help Manual

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