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: |
1.68 |
| 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), robust |
| LinkingTo: |
Rcpp |
| Suggests: |
org.Hs.eg.db, org.Mm.eg.db, infotheo, entropy, minet |
| Published: |
2019-05-23 |
| Author: |
Peter Langfelder and Steve Horvath with contributions by Chaochao Cai, Jun Dong, Jeremy Miller, Lin Song, Andy Yip, and Bin Zhang |
| Maintainer: |
Peter Langfelder <Peter.Langfelder at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
http://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/ |
| NeedsCompilation: |
yes |
| Citation: |
WGCNA citation info |
| Materials: |
ChangeLog |
| CRAN checks: |
WGCNA results |