DGCA                    DGCA: An R package for Differential Gene
                        Correlation Analysis
adjustPVals             Adjusts a numeric vector of p-values.
ages_darmanis           Brain sample ages vector.
bigEmpPVals             Use speed-optimized sorting to calculate
                        p-values observed and simulated null test
                        statistic using a reference pool distribution.
corMats-class           An S4 class to store correlation matrices and
                        associated info.
dCorAvg                 Get average empirical differential
                        correlations.
dCorClass               Classify differential correlations.
dCorMats                Finds differential correlations between
                        matrices.
dCorrs                  Differential correlation between two
                        conditions.
darmanis                Single-cell gene expression data from different
                        brain cell types.
dcPair-class            S4 class for pairwise differential correlation
                        matrices and associated info.
dcTopPairs              Creates a data frame for the top differentially
                        correlated gene pairs in your data set.
ddMEGENA                Integration function to use MEGENA to perform
                        network analyses of DGCA results.
ddcorAll                Calls the DGCA pairwise pipeline.
ddcorFindSignificant    Find groups of differentially correlated gene
                        symbols.
ddcorGO                 Gene ontology of differential
                        correlation-classified genes.
ddplot                  Create a heatmap showing the correlations in
                        two conditions.
design_mat              Design matrix of cell type specifications of
                        the single-cell RNA-seq samples.
extractModuleGO         Extract results from the module GO analysis
filterGenes             Filter rows out of a matrix.
findGOTermEnrichment    Find GO enrichment for a gene vector (using
                        GOstats).
getCors                 Compute matrices necessary for differential
                        correlation calculation.
getDCorPerm             Get permuted groupwise correlations and
                        pairwise differential correlations.
getDCors                Get groupwise correlations and pairwise
                        differential correlations.
getGroupsFromDesign     Split input matrix(es) based on the design
                        matrix.
makeDesign              Create a design matrix from a character vector.
matCorSig               Calculate correlation matrix p-values.
matCorr                 Calculate a correlation matrix.
matNSamp                Find the number of non-missing values.
moduleDC                Calculate modular differential connectivity
                        (MDC)
moduleGO                Perform module GO-trait correlation
pairwiseDCor            Calculate pairwise differential correlations.
permQValue              Calculate q-values from DGCA class objects
                        based on permutation-based empirical null
                        statistics.
plotCors                Plot gene pair correlations in multiple
                        conditions.
plotGOOneGroup          Plot results from a hypergeometric enrichment
                        test for one condition.
plotGOTwoGroups         Plot results from a hypergeometric enrichment
                        test to compare two conditions.
plotModuleGO            Plot extracted results from module-based GO
                        enrichment analysis using ggplot2.
plotVals                Creates a dotplot of the overall values for an
                        individual gene in multiple conditions.
switchGenesToHGCN       Switches a gene vector to cleaned HGNC symbols.
topDCGenes              Ranks genes by their total number of
                        differentially correlated gene pairs.
