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.
- Version1.0.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release01/22/2021
Documentation
Team
Daniel Osorio
Yan Zhong
Show author detailsRolesAuthor, ContributorGuanxun Li
Show author detailsRolesAuthor, ContributorQian Xu
Show author detailsRolesAuthor, ContributorAndrew Hillhouse
Show author detailsRolesAuthor, ContributorJingshu Chen
Show author detailsRolesAuthor, ContributorLaurie Davidson
Show author detailsRolesAuthor, ContributorYanan Tian
Show author detailsRolesAuthor, ContributorRobert Chapkin
Show author detailsRolesAuthor, ContributorJianhua Huang
Show author detailsRolesAuthor, ContributorJames Cai
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- Imports8 packages
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