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 ZhongShow author detailsRolesAuthor, Contributor
- Guanxun LiShow author detailsRolesAuthor, Contributor
- Qian XuShow author detailsRolesAuthor, Contributor
- Andrew HillhouseShow author detailsRolesAuthor, Contributor
- Jingshu ChenShow author detailsRolesAuthor, Contributor
- Laurie DavidsonShow author detailsRolesAuthor, Contributor
- Yanan TianShow author detailsRolesAuthor, Contributor
- Robert ChapkinShow author detailsRolesAuthor, Contributor
- Jianhua HuangShow author detailsRolesAuthor, Contributor
- James Cai
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- Imports5 packages
- Suggests1 package