Package: GNET2 1.23.0
Chen Chen
GNET2: Constructing gene regulatory networks from expression data through functional module inference
Cluster genes to functional groups with E-M process. Iteratively perform TF assigning and Gene assigning, until the assignment of genes did not change, or max number of iterations is reached.
Authors:
GNET2_1.23.0.tar.gz
GNET2_1.23.0.zip(r-4.5)GNET2_1.23.0.zip(r-4.4)GNET2_1.23.0.zip(r-4.3)
GNET2_1.23.0.tgz(r-4.4-x86_64)GNET2_1.23.0.tgz(r-4.4-arm64)GNET2_1.23.0.tgz(r-4.3-x86_64)GNET2_1.23.0.tgz(r-4.3-arm64)
GNET2_1.23.0.tar.gz(r-4.5-noble)GNET2_1.23.0.tar.gz(r-4.4-noble)
GNET2_1.23.0.tgz(r-4.4-emscripten)GNET2_1.23.0.tgz(r-4.3-emscripten)
GNET2.pdf |GNET2.html✨
GNET2/json (API)
NEWS
| # Install 'GNET2' in R: |
| install.packages('GNET2', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/chrischen1/gnet2/issues
On BioConductor:GNET2-1.23.0(bioc 3.21)GNET2-1.22.0(bioc 3.20)
geneexpressionregressionnetworknetworkinferencesoftwarecpp
Last updated 2 months agofrom:fb558f7520. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 29 2024 |
| R-4.5-win-x86_64 | OK | Nov 29 2024 |
| R-4.5-linux-x86_64 | OK | Nov 29 2024 |
| R-4.4-win-x86_64 | OK | Nov 29 2024 |
| R-4.4-mac-x86_64 | OK | Nov 29 2024 |
| R-4.4-mac-aarch64 | OK | Nov 29 2024 |
| R-4.3-win-x86_64 | OK | Nov 29 2024 |
| R-4.3-mac-x86_64 | OK | Nov 29 2024 |
| R-4.3-mac-aarch64 | OK | Nov 29 2024 |
Exports:build_modulebuild_moduleRbuild_moduleR_heuristicbuild_split_tablecalc_likelihood_scoreextract_edgesget_correlation_listgnetkneepointDetectionplot_gene_groupplot_group_correlationplot_treesave_gnetsimilarity_score
Dependencies:abindaskpassbase64encBiobaseBiocGenericsbitbit64bslibcachemclicliprcolorspacecpp11crayoncurldata.tableDelayedArrayDiagrammeRdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehighrhmshtmltoolshtmlwidgetshttrigraphIRangesisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplyrprettyunitsprogresspurrrR6rappdirsRColorBrewerRcppreadrreshape2rlangrmarkdownrstudioapiS4ArraysS4VectorssassscalesSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttinytextzdbUCSC.utilsutf8vctrsviridisLitevisNetworkvroomwithrxfunxgboostXVectoryamlzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit a regression tree. | build_module |
| Build regression tree. | build_moduleR |
| Build regression tree with splits are detemined by K-means heuristicly. | build_moduleR_heuristic |
| Build split table by K-means heuristicly. | build_split_table |
| Calculate Gaussian Likelihood score. | calc_likelihood_score |
| Extract the network from the gnet result | extract_edges |
| Calculate correlation within each group. | get_correlation_list |
| Run GNET2 | gnet |
| Knee point detection. | kneepointDetection |
| Plot a module | plot_gene_group |
| Plot the correlation of each group | plot_group_correlation |
| Plot the regression tree. | plot_tree |
| Save the GNET2 results | save_gnet |
| Compute the similarity from a predefined condition group | similarity_score |
