Weighted Correlation Network Analysis

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Documentation for package ‘WGCNA’ version 1.72-5

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A B C D E F G H I K L M N O P Q R S T U V W

-- A --

accuracyMeasures Accuracy measures for a 2x2 confusion matrix or for vectors of predicted and observed values.
addBlockToBlockwiseData Create, merge and expand BlockwiseData objects
addErrorBars Add error bars to a barplot.
addGrid Add grid lines to an existing plot.
addGuideLines Add vertical "guide lines" to a dendrogram plot
addTraitToMEs Add trait information to multi-set module eigengene structure
adjacency Calculate network adjacency
adjacency.fromSimilarity Calculate network adjacency
adjacency.polyReg Adjacency matrix based on polynomial regression
adjacency.splineReg Calculate network adjacency based on natural cubic spline regression
AFcorMI Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
alignExpr Align expression data with given vector
allocateJobs Divide tasks among workers
allowWGCNAThreads Allow and disable multi-threading for certain WGCNA calculations
automaticNetworkScreening One-step automatic network gene screening
automaticNetworkScreeningGS One-step automatic network gene screening with external gene significance

-- B --

BD.actualFileNames Various basic operations on 'BlockwiseData' objects.
BD.blockLengths Various basic operations on 'BlockwiseData' objects.
BD.checkAndDeleteFiles Various basic operations on 'BlockwiseData' objects.
BD.getData Various basic operations on 'BlockwiseData' objects.
BD.getMetaData Various basic operations on 'BlockwiseData' objects.
BD.nBlocks Various basic operations on 'BlockwiseData' objects.
bicor Biweight Midcorrelation
bicorAndPvalue Calculation of biweight midcorrelations and associated p-values
bicovWeightFactors Weights used in biweight midcovariance
bicovWeights Weights used in biweight midcovariance
bicovWeightsFromFactors Weights used in biweight midcovariance
binarizeCategoricalColumns Turn categorical columns into sets of binary indicators
binarizeCategoricalColumns.forPlots Turn categorical columns into sets of binary indicators
binarizeCategoricalColumns.forRegression Turn categorical columns into sets of binary indicators
binarizeCategoricalColumns.pairwise Turn categorical columns into sets of binary indicators
binarizeCategoricalVariable Turn a categorical variable into a set of binary indicators
BlockInformation Create a list holding information about dividing data into blocks
blockSize Attempt to calculate an appropriate block size to maximize efficiency of block-wise calcualtions.
blockwiseConsensusModules Find consensus modules across several datasets.
BlockwiseData Create, merge and expand BlockwiseData objects
blockwiseIndividualTOMs Calculation of block-wise topological overlaps
blockwiseModules Automatic network construction and module detection
BloodLists Blood Cell Types with Corresponding Gene Markers
blueWhiteRed Blue-white-red color sequence
BrainLists Brain-Related Categories with Corresponding Gene Markers
BrainRegionMarkers Gene Markers for Regions of the Human Brain
branchEigengeneDissim Branch dissimilarity based on eigennodes (eigengenes).
branchEigengeneSimilarity Branch dissimilarity based on eigennodes (eigengenes).
branchSplit Branch split.
branchSplit.dissim Branch split based on dissimilarity.
branchSplitFromStabilityLabels Branch split (dissimilarity) statistics derived from labels determined from a stability study
branchSplitFromStabilityLabels.individualFraction Branch split (dissimilarity) statistics derived from labels determined from a stability study
branchSplitFromStabilityLabels.prediction Branch split (dissimilarity) statistics derived from labels determined from a stability study

-- C --

checkAdjMat Check adjacency matrix
checkSets Check structure and retrieve sizes of a group of datasets.
checkSimilarity Check adjacency matrix
chooseOneHubInEachModule Chooses a single hub gene in each module
chooseTopHubInEachModule Chooses the top hub gene in each module
clusterCoef Clustering coefficient calculation
coClustering Co-clustering measure of cluster preservation between two clusterings
coClustering.permutationTest Permutation test for co-clustering
collapseRows Select one representative row per group
collapseRowsUsingKME Selects one representative row per group based on kME
collectGarbage Iterative garbage collection.
colQuantileC Fast colunm- and row-wise quantile of a matrix.
conformityBasedNetworkConcepts Calculation of conformity-based network concepts.
conformityDecomposition Conformity and module based decomposition of a network adjacency matrix.
consensusCalculation Calculation of a (single) consenus with optional data calibration.
consensusDissTOMandTree Consensus clustering based on topological overlap and hierarchical clustering
consensusKME Calculate consensus kME (eigengene-based connectivities) across multiple data sets.
consensusMEDissimilarity Consensus dissimilarity of module eigengenes.
ConsensusOptions Create a list holding consensus calculation options.
consensusOrderMEs Put close eigenvectors next to each other in several sets.
consensusProjectiveKMeans Consensus projective K-means (pre-)clustering of expression data
consensusRepresentatives Consensus selection of group representatives
consensusTOM Consensus network (topological overlap).
ConsensusTree Create a new consensus tree
consensusTreeInputs Get all elementary inputs in a consensus tree
convertNumericColumnsToNumeric Convert character columns that represent numbers to numeric
cor Fast calculations of Pearson correlation.
cor1 Fast calculations of Pearson correlation.
corAndPvalue Calculation of correlations and associated p-values
corFast Fast calculations of Pearson correlation.
corPredictionSuccess Qunatification of success of gene screening
corPvalueFisher Fisher's asymptotic p-value for correlation
corPvalueStudent Student asymptotic p-value for correlation
CorrelationOptions Creates a list of correlation options.
correlationPreservation Preservation of eigengene correlations
coxRegressionResiduals Deviance- and martingale residuals from a Cox regression model
cutreeStatic Constant-height tree cut
cutreeStaticColor Constant height tree cut using color labels

-- D --

disableWGCNAThreads Allow and disable multi-threading for certain WGCNA calculations
displayColors Show colors used to label modules
dynamicMergeCut Threshold for module merging

-- E --

empiricalBayesLM Empirical Bayes-moderated adjustment for unwanted covariates
enableWGCNAThreads Allow and disable multi-threading for certain WGCNA calculations
exportNetworkToCytoscape Export network to Cytoscape
exportNetworkToVisANT Export network data in format readable by VisANT

-- F --

factorizeNonNumericColumns Turn non-numeric columns into factors
fixDataStructure Put single-set data into a form useful for multiset calculations.
formatLabels Break long character strings into multiple lines
fundamentalNetworkConcepts Calculation of fundamental network concepts from an adjacency matrix.

-- G --

GOenrichmentAnalysis Calculation of GO enrichment (experimental)
goodGenes Filter genes with too many missing entries
goodGenesMS Filter genes with too many missing entries across multiple sets
goodSamples Filter samples with too many missing entries
goodSamplesGenes Iterative filtering of samples and genes with too many missing entries
goodSamplesGenesMS Iterative filtering of samples and genes with too many missing entries across multiple data sets
goodSamplesMS Filter samples with too many missing entries across multiple data sets
greenBlackRed Green-black-red color sequence
greenWhiteRed Green-white-red color sequence
GTOMdist Generalized Topological Overlap Measure

-- H --

hierarchicalBranchEigengeneDissim Branch dissimilarity based on eigennodes (eigengenes).
hierarchicalConsensusCalculation Hierarchical consensus calculation
hierarchicalConsensusKME Calculation of measures of fuzzy module membership (KME) in hierarchical consensus modules
hierarchicalConsensusMEDissimilarity Hierarchical consensus calculation of module eigengene dissimilarity
hierarchicalConsensusModules Hierarchical consensus network construction and module identification
hierarchicalConsensusTOM Calculation of hierarchical consensus topological overlap matrix
hierarchicalMergeCloseModules Merge close (similar) hierarchical consensus modules
hubGeneSignificance Hubgene significance

-- I --

ImmunePathwayLists Immune Pathways with Corresponding Gene Markers
imputeByModule Impute missing data separately in each module
individualTOMs Calculate individual correlation network matrices
initProgInd Inline display of progress
intramodularConnectivity Calculation of intramodular connectivity
intramodularConnectivity.fromExpr Calculation of intramodular connectivity
isMultiData Determine whether the supplied object is a valid multiData structure

-- K --

keepCommonProbes Keep probes that are shared among given data sets
kMEcomparisonScatterplot Function to plot kME values between two comparable data sets.

-- L --

labeledBarplot Barplot with text or color labels.
labeledHeatmap Produce a labeled heatmap plot
labeledHeatmap.multiPage Labeled heatmap divided into several separate plots.
labelPoints Label scatterplot points
labels2colors Convert numerical labels to colors.
list2multiData Convert a list to a multiData structure and vice-versa.
lowerTri2matrix Reconstruct a symmetric matrix from a distance (lower-triangular) representation

-- M --

matchLabels Relabel module labels to best match the given reference labels
matrixToNetwork Construct a network from a matrix
mergeBlockwiseData Create, merge and expand BlockwiseData objects
mergeCloseModules Merge close modules in gene expression data
metaAnalysis Meta-analysis of binary and continuous variables
metaZfunction Meta-analysis Z statistic
minWhichMin Fast joint calculation of row- or column-wise minima and indices of minimum elements
moduleColor.getMEprefix Get the prefix used to label module eigengenes.
moduleEigengenes Calculate module eigengenes.
moduleMergeUsingKME Merge modules and reassign genes using kME.
moduleNumber Fixed-height cut of a dendrogram.
modulePreservation Calculation of module preservation statistics
mtd.apply Apply a function to each set in a multiData structure.
mtd.applyToSubset Apply a function to each set in a multiData structure.
mtd.branchEigengeneDissim Branch dissimilarity based on eigennodes (eigengenes).
mtd.colnames Get and set column names in a multiData structure.
mtd.mapply Apply a function to elements of given multiData structures.
mtd.rbindSelf Turn a multiData structure into a single matrix or data frame.
mtd.setAttr Set attributes on each component of a multiData structure
mtd.setColnames Get and set column names in a multiData structure.
mtd.simplify If possible, simplify a multiData structure to a 3-dimensional array.
mtd.subset Subset rows and columns in a multiData structure
multiData Create a multiData structure.
multiData.eigengeneSignificance Eigengene significance across multiple sets
multiData2list Convert a list to a multiData structure and vice-versa.
multiGrep Analogs of grep(l) and (g)sub for multiple patterns and relacements
multiGrepl Analogs of grep(l) and (g)sub for multiple patterns and relacements
multiGSub Analogs of grep(l) and (g)sub for multiple patterns and relacements
multiIntersect Union and intersection of multiple sets
multiSetMEs Calculate module eigengenes.
multiSub Analogs of grep(l) and (g)sub for multiple patterns and relacements
multiUnion Union and intersection of multiple sets
mutualInfoAdjacency Calculate weighted adjacency matrices based on mutual information

-- N --

nearestCentroidPredictor Nearest centroid predictor
nearestNeighborConnectivity Connectivity to a constant number of nearest neighbors
nearestNeighborConnectivityMS Connectivity to a constant number of nearest neighbors across multiple data sets
networkConcepts Calculations of network concepts
NetworkOptions Create a list of network construction arguments (options).
networkScreening Identification of genes related to a trait
networkScreeningGS Network gene screening with an external gene significance measure
newBlockInformation Create a list holding information about dividing data into blocks
newBlockwiseData Create, merge and expand BlockwiseData objects
newConsensusOptions Create a list holding consensus calculation options.
newConsensusTree Create a new consensus tree
newCorrelationOptions Creates a list of correlation options.
newNetworkOptions Create a list of network construction arguments (options).
normalizeLabels Transform numerical labels into normal order.
nPresent Number of present data entries.
nSets Number of sets in a multi-set variable
numbers2colors Color representation for a numeric variable

-- O --

orderBranchesUsingHubGenes Optimize dendrogram using branch swaps and reflections.
orderMEs Put close eigenvectors next to each other
orderMEsByHierarchicalConsensus Order module eigengenes by their hierarchical consensus similarity
overlapTable Calculate overlap of modules
overlapTableUsingKME Determines significant overlap between modules in two networks based on kME tables.

-- P --

pickHardThreshold Analysis of scale free topology for hard-thresholding.
pickHardThreshold.fromSimilarity Analysis of scale free topology for hard-thresholding.
pickSoftThreshold Analysis of scale free topology for soft-thresholding
pickSoftThreshold.fromSimilarity Analysis of scale free topology for soft-thresholding
plotClusterTreeSamples Annotated clustering dendrogram of microarray samples
plotColorUnderTree Plot color rows in a given order, for example under a dendrogram
plotCor Red and Green Color Image of Correlation Matrix
plotDendroAndColors Dendrogram plot with color annotation of objects
plotEigengeneNetworks Eigengene network plot
plotMat Red and Green Color Image of Data Matrix
plotMEpairs Pairwise scatterplots of eigengenes
plotModuleSignificance Barplot of module significance
plotMultiHist Plot multiple histograms in a single plot
plotNetworkHeatmap Network heatmap plot
plotOrderedColors Plot color rows in a given order, for example under a dendrogram
pmean Parallel quantile, median, mean
pmean.fromList Parallel quantile, median, mean
pmedian Parallel quantile, median, mean
pminWhich.fromList Parallel quantile, median, mean
populationMeansInAdmixture Estimate the population-specific mean values in an admixed population.
pquantile Parallel quantile, median, mean
pquantile.fromList Parallel quantile, median, mean
prepComma Prepend a comma to a non-empty string
prependZeros Pad numbers with leading zeros to specified total width
prependZeros.int Pad numbers with leading zeros to specified total width
preservationNetworkConnectivity Network preservation calculations
projectiveKMeans Projective K-means (pre-)clustering of expression data
proportionsInAdmixture Estimate the proportion of pure populations in an admixed population based on marker expression values.
propVarExplained Proportion of variance explained by eigengenes.
pruneAndMergeConsensusModules Iterative pruning and merging of (hierarchical) consensus modules
pruneConsensusModules Prune (hierarchical) consensus modules by removing genes with low eigengene-based intramodular connectivity
PWLists Pathways with Corresponding Gene Markers - Compiled by Mike Palazzolo and Jim Wang from CHDI

-- Q --

qvalue Estimate the q-values for a given set of p-values
qvalue.restricted qvalue convenience wrapper

-- R --

randIndex Rand index of two partitions
rankPvalue Estimate the p-value for ranking consistently high (or low) on multiple lists
recutBlockwiseTrees Repeat blockwise module detection from pre-calculated data
recutConsensusTrees Repeat blockwise consensus module detection from pre-calculated data
redWhiteGreen Red-white-green color sequence
reflectBranch Select, swap, or reflect branches in a dendrogram.
relativeCorPredictionSuccess Compare prediction success
removeGreyME Removes the grey eigengene from a given collection of eigengenes.
removePrincipalComponents Remove leading principal components from data
replaceMissing Replace missing values with a constant.
returnGeneSetsAsList Return pre-defined gene lists in several biomedical categories.
rgcolors.func Red and Green Color Specification
rowQuantileC Fast colunm- and row-wise quantile of a matrix.

-- S --

sampledBlockwiseModules Blockwise module identification in sampled data
sampledHierarchicalConsensusModules Hierarchical consensus module identification in sampled data
scaleFreeFitIndex Calculation of fitting statistics for evaluating scale free topology fit.
scaleFreePlot Visual check of scale-free topology
SCsLists Stem Cell-Related Genes with Corresponding Gene Markers
selectBranch Select, swap, or reflect branches in a dendrogram.
selectFewestConsensusMissing Select columns with the lowest consensus number of missing data
setCorrelationPreservation Summary correlation preservation measure
shortenStrings Shorten given character strings by truncating at a suitable separator.
sigmoidAdjacencyFunction Sigmoid-type adacency function.
signedKME Signed eigengene-based connectivity
signifNumeric Round numeric columns to given significant digits.
signumAdjacencyFunction Hard-thresholding adjacency function
simpleConsensusCalculation Simple calculation of a single consenus
simpleHierarchicalConsensusCalculation Simple hierarchical consensus calculation
simulateDatExpr Simulation of expression data
simulateDatExpr5Modules Simplified simulation of expression data
simulateEigengeneNetwork Simulate eigengene network from a causal model
simulateModule Simulate a gene co-expression module
simulateMultiExpr Simulate multi-set expression data
simulateSmallLayer Simulate small modules
sizeGrWindow Opens a graphics window with specified dimensions
sizeRestrictedClusterMerge Cluter merging with size restrictions
softConnectivity Calculates connectivity of a weighted network.
softConnectivity.fromSimilarity Calculates connectivity of a weighted network.
spaste Space-less paste
standardColors Colors this library uses for labeling modules.
standardScreeningBinaryTrait Standard screening for binatry traits
standardScreeningCensoredTime Standard Screening with regard to a Censored Time Variable
standardScreeningNumericTrait Standard screening for numeric traits
stdErr Standard error of the mean of a given vector.
stratifiedBarplot Bar plots of data across two splitting parameters
subsetTOM Topological overlap for a subset of a whole set of genes
swapTwoBranches Select, swap, or reflect branches in a dendrogram.

-- T --

TOMdist Topological overlap matrix similarity and dissimilarity
TOMplot Graphical representation of the Topological Overlap Matrix
TOMsimilarity Topological overlap matrix similarity and dissimilarity
TOMsimilarityFromExpr Topological overlap matrix
transposeBigData Transpose a big matrix or data frame
TrueTrait Estimate the true trait underlying a list of surrogate markers.

-- U --

unsignedAdjacency Calculation of unsigned adjacency
updateProgInd Inline display of progress
userListEnrichment Measure enrichment between inputted and user-defined lists

-- V --

vectorizeMatrix Turn a matrix into a vector of non-redundant components
vectorTOM Topological overlap for a subset of the whole set of genes
verboseBarplot Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
verboseBoxplot Boxplot annotated by a Kruskal-Wallis p-value
verboseIplot Scatterplot with density
verboseScatterplot Scatterplot annotated by regression line and p-value
votingLinearPredictor Voting linear predictor

-- W --

WGCNAnThreads Allow and disable multi-threading for certain WGCNA calculations