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:Chen Chen, Jie Hou and Jianlin Cheng

GNET2_1.23.0.tar.gz
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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

Uses libs:

c++– GNU Standard C++ Library v3

On BioConductor:GNET2-1.21.0(bioc 3.20)GNET2-1.20.0(bioc 3.19)

geneexpression regression network networkinference software

4.60 score 2 stars 3 scripts 138 downloads 14 exports 99 dependencies

Last updated 23 days agofrom:fb558f7520. Checks:OK: 9. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 30 2024
R-4.5-win-x86_64	OK	Oct 30 2024
R-4.5-linux-x86_64	OK	Oct 30 2024
R-4.4-win-x86_64	OK	Oct 30 2024
R-4.4-mac-x86_64	OK	Oct 31 2024
R-4.4-mac-aarch64	OK	Oct 31 2024
R-4.3-win-x86_64	OK	Oct 30 2024
R-4.3-mac-x86_64	OK	Oct 31 2024
R-4.3-mac-aarch64	OK	Oct 31 2024

Exports:build_module build_moduleR build_moduleR_heuristic build_split_table calc_likelihood_score extract_edges get_correlation_list gnet kneepointDetection plot_gene_group plot_group_correlation plot_tree save_gnet similarity_score

Dependencies:abind askpass base64enc Biobase BiocGenerics bit bit64 bslib cachem cli clipr colorspace cpp11 crayon curl data.table DelayedArray DiagrammeR digest dplyr evaluate fansi farver fastmap fontawesome fs generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue gtable highr hms htmltools htmlwidgets httr igraph IRanges isoband jquerylib jsonlite knitr labeling lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime munsell nlme openssl pillar pkgconfig plyr prettyunits progress purrr R6 rappdirs RColorBrewer Rcpp readr reshape2 rlang rmarkdown rstudioapi S4Arrays S4Vectors sass scales SparseArray stringi stringr SummarizedExperiment sys tibble tidyr tidyselect tinytex tzdb UCSC.utils utf8 vctrs viridisLite visNetwork vroom withr xfun xgboost XVector yaml zlibbioc

Build functional gene modules with GNET2

Chen Chen

Rendered fromrun_gnet2.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2020-10-17
Started: 2019-03-27

Citation

Development and contributors

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