Functions necessary to perform Weighted Correlation
Network Analysis.

R (>= 2.14), dynamicTreeCut (>= 1.60), flashClust, Hmisc
stats, impute, grDevices, utils, splines, reshape, foreach,
doParallel, matrixStats (>= 0.8.1)
Functions necessary to perform Weighted Correlation Network Analysis.

R (>= 2.14), dynamicTreeCut (>= 1.62), flashClust
stats, grDevices, utils, matrixStats (>= 0.8.1), Hmisc,
impute, splines, foreach, doParallel, reshape

R (>= 2.14), dynamicTreeCut (>= 1.62), fastcluster
stats, grDevices, utils, matrixStats (>= 0.8.1), Hmisc,
impute, splines, foreach, doParallel, reshape, preprocessCore,
survival, parallel
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.

stats, grDevices, utils, matrixStats (>= 0.8.1), Hmisc,
impute, splines, foreach, doParallel, reshape, preprocessCore,
survival, parallel, GO.db, AnnotationDbi
org.Hs.eg.db, org.Mm.eg.db, infotheo, entropy, minet

R (>= 3.0), dynamicTreeCut (>= 1.62), fastcluster

stats, grDevices, utils, matrixStats (>= 0.8.1), Hmisc,
impute, splines, foreach, doParallel, preprocessCore, survival,
parallel, GO.db, AnnotationDbi

stats, grDevices, utils, matrixStats (>= 0.8.1), Hmisc,
impute, splines, foreach, doParallel, preprocessCore, survival,
parallel, GO.db, AnnotationDbi, Rcpp (>= 0.11.0), robust

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.