Package: EGRNi 0.1.6
EGRNi: Ensemble Gene Regulatory Network Inference
Gene regulatory network constructed using combined score obtained from individual network inference method. The combined score measures the significance of edges in the ensemble network. Fisher's weighted method has been implemented to combine the outcomes of different methods based on the probability values. The combined score follows chi-square distribution with 2n degrees of freedom. <doi:10.22271/09746315.2020.v16.i3.1358>.
Authors:
EGRNi_0.1.6.tar.gz
EGRNi_0.1.6.zip(r-4.5)EGRNi_0.1.6.zip(r-4.4)EGRNi_0.1.6.zip(r-4.3)
EGRNi_0.1.6.tgz(r-4.4-any)EGRNi_0.1.6.tgz(r-4.3-any)
EGRNi_0.1.6.tar.gz(r-4.5-noble)EGRNi_0.1.6.tar.gz(r-4.4-noble)
EGRNi_0.1.6.tgz(r-4.4-emscripten)EGRNi_0.1.6.tgz(r-4.3-emscripten)
EGRNi.pdf |EGRNi.html✨
EGRNi/json (API)
| # Install 'EGRNi' in R: |
| install.packages('EGRNi', repos = c('https://chiranjibsbioinfo.r-universe.dev', 'https://cloud.r-project.org')) |
- Edgescore - Edge score obtained from 4 different methods for Ensemble Gene Regulatory Network Inference
- gene_exp - Gene expression data for Ensemble Gene Regulatory Network Inference
- pvalue - Probability values for Ensemble Gene Regulatory Network Inference
- weight - Weights for Ensemble Gene Regulatory Network Inference
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:07b2e2ed77. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 13 2024 |
| R-4.5-win | OK | Nov 13 2024 |
| R-4.5-linux | OK | Nov 13 2024 |
| R-4.4-win | OK | Nov 13 2024 |
| R-4.4-mac | OK | Nov 13 2024 |
| R-4.3-win | OK | Nov 13 2024 |
| R-4.3-mac | OK | Nov 13 2024 |
Exports:CRNEdg2FwEdgescoreEGRNF_scoregene_expIntsctEdg2FwPCNPLSNpvalueRidgNweight
Dependencies:bitbit64clicliprcpp11crayonfansifdrtoolgdatagluegtoolshmslifecyclemagrittrMASSpillarpkgconfigprettyunitsprogressR6readrrlangtibbletidyselecttzdbutf8vctrsvroomwithr
