Performs differential correlation analysis on input matrices, with multiple conditions specified by a design matrix. Contains functions to filter, process, save, visualize, and interpret differential correlations of identifier-pairs across the entire identifier space, or with respect to a particular set of identifiers (e.g., one). Also contains several functions to perform differential correlation analysis on clusters (i.e., modules) or genes. Finally, it contains functions to generate empirical p-values for the hypothesis tests and adjust them for multiple comparisons. Although the package was built with gene expression data in mind, it is applicable to other types of genomics data as well, in addition to being potentially applicable to data from other fields entirely. It is described more fully in the manuscript introducing it, freely available at .

Documentation

Manual: DGCA.pdf
Vignette: Basic DGCA Vignette

Maintainer: Andrew McKenzie <amckenz at gmail.com>

Author(s): Bin Zhang*, Andrew McKenzie*

Install package and any missing dependencies by running this line in your R console:

install.packages("DGCA")

Depends R (>= 3.2)
Imports WGCNA, matrixStats, methods
Suggests knitr, impute, gplots, fdrtool, testthat, ggplot2, plotrix, GOstats, HGNChelper, org.Hs.eg.db, AnnotationDbi, abind, MEGENA, Matrix, doMC, igraph, cowplot, stats, utils
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Package DGCA
Materials
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Version 1.0.1
Published 2016-11-17
License GPL-3
BugReports
SystemRequirements
NeedsCompilation no
Citation
CRAN checks DGCA check results
Package source DGCA_1.0.1.tar.gz