Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Version: 1.73 Depends: R (≥ 3.0), dynamicTreeCut (≥ 1.62), fastcluster Imports: stats, grDevices, utils, matrixStats (≥ 0.8.1), Hmisc, impute, splines, foreach, doParallel, preprocessCore, survival, parallel, GO.db, AnnotationDbi, Rcpp (≥ 0.11.0) LinkingTo: Rcpp Suggests: org.Hs.eg.db, org.Mm.eg.db, infotheo, entropy, minet Published: 2024-09-18 DOI: 10.32614/CRAN.package.WGCNA Author: Peter Langfelder [aut, cre], Steve Horvath [aut], Chaochao Cai [aut], Jun Dong [aut], Jeremy Miller [aut], Lin Song [aut], Andy Yip [aut], Bin Zhang [aut] Maintainer: Peter Langfelder <Peter.Langfelder at gmail.com> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: yes Citation: WGCNA citation info Materials: ChangeLog In views: NetworkAnalysis, Omics CRAN checks: WGCNA resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4