Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data. 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: |
1.48 |
| 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 |
| Suggests: |
org.Hs.eg.db, org.Mm.eg.db, infotheo, entropy, minet |
| Published: |
2015-10-30 |
| 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://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA/ |
| NeedsCompilation: |
yes |
| Citation: |
WGCNA citation info |
| Materials: |
ChangeLog |
| CRAN checks: |
WGCNA results |