# WGCNA v1.68

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## Weighted Correlation Network Analysis

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.

## Functions in WGCNA

Name | Description | |

GTOMdist | Generalized Topological Overlap Measure | |

TOMsimilarityFromExpr | Topological overlap matrix | |

alignExpr | Align expression data with given vector | |

allocateJobs | Divide tasks among workers | |

TrueTrait | Estimate the true trait underlying a list of surrogate markers. | |

blockwiseIndividualTOMs | Calculation of block-wise topological overlaps | |

blockwiseModules | Automatic network construction and module detection | |

branchSplitFromStabilityLabels | Branch split (dissimilarity) statistics derived from labels determined from a stability study | |

checkAdjMat | Check adjacency matrix | |

consensusOrderMEs | Put close eigenvectors next to each other in several sets. | |

consensusProjectiveKMeans | Consensus projective K-means (pre-)clustering of expression data | |

consensusTreeInputs | Get all elementary inputs in a consensus tree | |

convertNumericColumnsToNumeric | Convert character columns that represent numbers to numeric | |

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. | |

PWLists | Pathways with Corresponding Gene Markers - Compiled by Mike Palazzolo and Jim Wang from CHDI | |

hierarchicalConsensusCalculation | Hierarchical consensus calculation | |

SCsLists | Stem Cell-Related Genes with Corresponding Gene Markers | |

hierarchicalConsensusKME | Calculation of measures of fuzzy module membership (KME) in hierarchical consensus modules | |

labelPoints | Label scatterplot points | |

TOMplot | Graphical representation of the Topological Overlap Matrix | |

labeledBarplot | Barplot with text or color labels. | |

TOMsimilarity | Topological overlap matrix similarity and dissimilarity | |

metaAnalysis | Meta-analysis of binary and continuous variables | |

metaZfunction | Meta-analysis Z statistic | |

bicorAndPvalue | Calculation of biweight midcorrelations and associated p-values | |

bicovWeights | Weights used in biweight midcovariance | |

binarizeCategoricalColumns | Turn categorical columns into sets of binary indicators | |

binarizeCategoricalVariable | Turn a categorical variable into a set of binary indicators | |

mtd.rbindSelf | Turn a multiData structure into a single matrix or data frame. | |

chooseTopHubInEachModule | Chooses the top hub gene in each module | |

clusterCoef | Clustering coefficient calculation | |

collapseRowsUsingKME | Selects one representative row per group based on kME | |

collectGarbage | Iterative garbage collection. | |

mtd.setAttr | Set attributes on each component of a multiData structure | |

multiSetMEs | Calculate module eigengenes. | |

consensusRepresentatives | Consensus selection of group representatives | |

consensusTOM | Consensus network (topological overlap). | |

multiUnion | Union and intersection of multiple sets | |

exportNetworkToCytoscape | Export network to Cytoscape | |

BrainRegionMarkers | Gene Markers for Regions of the Human Brain | |

exportNetworkToVisANT | Export network data in format readable by VisANT | |

newNetworkOptions | Create a list of network construction arguments (options). | |

greenBlackRed | Green-black-red color sequence | |

greenWhiteRed | Green-white-red color sequence | |

normalizeLabels | Transform numerical labels into normal order. | |

BloodLists | Blood Cell Types with Corresponding Gene Markers | |

hubGeneSignificance | Hubgene significance | |

imputeByModule | Impute missing data separately in each module | |

labels2colors | Convert numerical labels to colors. | |

pickHardThreshold | Analysis of scale free topology for hard-thresholding. | |

accuracyMeasures | Accuracy measures for a 2x2 confusion matrix or for vectors of predicted and observed values. | |

GOenrichmentAnalysis | Calculation of GO enrichment (experimental) | |

BrainLists | Brain-Related Categories with Corresponding Gene Markers | |

addErrorBars | Add error bars to a barplot. | |

allowWGCNAThreads | Allow and disable multi-threading for certain WGCNA calculations | |

pickSoftThreshold | Analysis of scale free topology for soft-thresholding | |

plotMat | Red and Green Color Image of Data Matrix | |

projectiveKMeans | Projective K-means (pre-)clustering of expression data | |

plotModuleSignificance | Barplot of module significance | |

list2multiData | Convert a list to a multiData structure and vice-versa. | |

preservationNetworkConnectivity | Network preservation calculations | |

minWhichMin | Fast joint calculation of row- or column-wise minima and indices of minimum elements | |

addTraitToMEs | Add trait information to multi-set module eigengene structure | |

adjacency | Calculate network adjacency | |

adjacency.polyReg | Adjacency matrix based on polynomial regression | |

automaticNetworkScreening | One-step automatic network gene screening | |

AFcorMI | Prediction of Weighted Mutual Information Adjacency Matrix by Correlation | |

moduleNumber | Fixed-height cut of a dendrogram. | |

moduleColor.getMEprefix | Get the prefix used to label module eigengenes. | |

modulePreservation | Calculation of module preservation statistics | |

branchSplit | Branch split. | |

branchSplit.dissim | Branch split based on dissimilarity. | |

checkSets | Check structure and retrieve sizes of a group of datasets. | |

chooseOneHubInEachModule | Chooses a single hub gene in each module | |

redWhiteGreen | Red-white-green color sequence | |

conformityBasedNetworkConcepts | Calculation of conformity-based network concepts. | |

blockSize | Attempt to calculate an appropriate block size to maximize efficiency of block-wise calcualtions. | |

adjacency.splineReg | Calculate network adjacency based on natural cubic spline regression | |

conformityDecomposition | Conformity and module based decomposition of a network adjacency matrix. | |

corPvalueStudent | Student asymptotic p-value for correlation | |

BD.getData | Various basic operations on BlockwiseData objects. | |

correlationPreservation | Preservation of eigengene correlations | |

addGrid | Add grid lines to an existing plot. | |

addGuideLines | Add vertical ``guide lines'' to a dendrogram plot | |

automaticNetworkScreeningGS | One-step automatic network gene screening with external gene significance | |

coxRegressionResiduals | Deviance- and martingale residuals from a Cox regression model | |

cutreeStatic | Constant-height tree cut | |

blockwiseConsensusModules | Find consensus modules across several datasets. | |

relativeCorPredictionSuccess | Compare prediction success | |

goodSamples | Filter samples with too many missing entries | |

coClustering | Co-clustering measure of cluster preservation between two clusterings | |

goodSamplesGenes | Iterative filtering of samples and genes with too many missing entries | |

individualTOMs | Calculate individual correlation network matrices | |

nSets | Number of sets in a multi-set variable | |

nearestCentroidPredictor | Nearest centroid predictor | |

newConsensusTree | Create a new consensus tree | |

newCorrelationOptions | Creates a list of correlation options. | |

bicor | Biweight Midcorrelation | |

scaleFreePlot | Visual check of scale-free topology | |

blueWhiteRed | Blue-white-red color sequence | |

selectFewestConsensusMissing | Select columns with the lowest consensus number of missing data | |

coClustering.permutationTest | Permutation test for co-clustering | |

numbers2colors | Color representation for a numeric variable | |

colQuantileC | Fast colunm- and row-wise quantile of a matrix. | |

Inline display of progress | Inline display of progress | |

branchEigengeneDissim | Branch dissimilarity based on eigennodes (eigengenes). | |

collapseRows | Select one representative row per group | |

intramodularConnectivity | Calculation of intramodular connectivity | |

consensusKME | Calculate consensus kME (eigengene-based connectivities) across multiple data sets. | |

consensusCalculation | Calculation of a (single) consenus with optional data calibration. | |

consensusMEDissimilarity | Consensus dissimilarity of module eigengenes. | |

corPredictionSuccess | Qunatification of success of gene screening | |

orderBranchesUsingHubGenes | Optimize dendrogram using branch swaps and reflections. | |

plotEigengeneNetworks | Eigengene network plot | |

consensusDissTOMandTree | Consensus clustering based on topological overlap and hierarchical clustering | |

isMultiData | Determine whether the supplied object is a valid multiData structure | |

corPvalueFisher | Fisher's asymptotic p-value for correlation | |

lowerTri2matrix | Reconstruct a symmetric matrix from a distance (lower-triangular) representation | |

cor | Fast calculations of Pearson correlation. | |

plotMEpairs | Pairwise scatterplots of eigengenes | |

matchLabels | Relabel module labels to best match the given reference labels | |

propVarExplained | Proportion of variance explained by eigengenes. | |

corAndPvalue | Calculation of correlations and associated p-values | |

dynamicMergeCut | Threshold for module merging | |

mtd.apply | Apply a function to each set in a multiData structure. | |

proportionsInAdmixture | Estimate the proportion of pure populations in an admixed population based on marker expression values. | |

mtd.mapply | Apply a function to elements of given multiData structures. | |

nearestNeighborConnectivity | Connectivity to a constant number of nearest neighbors | |

cutreeStaticColor | Constant height tree cut using color labels | |

displayColors | Show colors used to label modules | |

recutBlockwiseTrees | Repeat blockwise module detection from pre-calculated data | |

goodGenes | Filter genes with too many missing entries | |

empiricalBayesLM | Empirical Bayes-moderated adjustment for unwanted covariates | |

goodSamplesGenesMS | Iterative filtering of samples and genes with too many missing entries across multiple data sets | |

goodGenesMS | Filter genes with too many missing entries across multiple sets | |

simulateEigengeneNetwork | Simulate eigengene network from a causal model | |

goodSamplesMS | Filter samples with too many missing entries across multiple data sets | |

nearestNeighborConnectivityMS | Connectivity to a constant number of nearest neighbors across multiple data sets | |

hierarchicalConsensusTOM | Calculation of hierarchical consensus topological overlap matrix | |

networkScreeningGS | Network gene screening with an external gene significance measure | |

simulateModule | Simulate a gene co-expression module | |

newBlockInformation | Create a list holding information about dividing data into blocks | |

recutConsensusTrees | Repeat blockwise consensus module detection from pre-calculated data | |

hierarchicalMergeCloseModules | Merge close (similar) hierarchical consensus modules | |

labeledHeatmap | Produce a labeled heatmap plot | |

hierarchicalConsensusMEDissimilarity | Hierarchical consensus calculation of module eigengene dissimilarity | |

overlapTable | Calculate overlap of modules | |

overlapTableUsingKME | Determines significant overlap between modules in two networks based on kME tables. | |

kMEcomparisonScatterplot | Function to plot kME values between two comparable data sets. | |

hierarchicalConsensusModules | Hierarchical consensus network construction and module identification | |

keepCommonProbes | Keep probes that are shared among given data sets | |

stdErr | Standard error of the mean of a given vector. | |

labeledHeatmap.multiPage | Labeled heatmap divided into several separate plots. | |

sigmoidAdjacencyFunction | Sigmoid-type adacency function. | |

moduleEigengenes | Calculate module eigengenes. | |

signedKME | Signed eigengene-based connectivity | |

matrixToNetwork | Construct a network from a matrix | |

moduleMergeUsingKME | Merge modules and reassign genes using kME. | |

stratifiedBarplot | Bar plots of data across two splitting parameters | |

userListEnrichment | Measure enrichment between inputted and user-defined lists | |

mergeCloseModules | Merge close modules in gene expression data | |

mtd.setColnames | Get and set column names in a multiData structure. | |

populationMeansInAdmixture | Estimate the population-specific mean values in an admixed population. | |

vectorTOM | Topological overlap for a subset of the whole set of genes | |

mtd.simplify | If possible, simplify a multiData structure to a 3-dimensional array. | |

pquantile | Parallel quantile, median, mean | |

multiData.eigengeneSignificance | Eigengene significance across multiple sets | |

simulateDatExpr | Simulation of expression data | |

mtd.subset | Subset rows and columns in a multiData structure | |

multiData | Create a multiData structure. | |

multiGSub | Analogs of grep(l) and (g)sub for multiple patterns and relacements | |

networkConcepts | Calculations of network concepts | |

simulateDatExpr5Modules | Simplified simulation of expression data | |

mutualInfoAdjacency | Calculate weighted adjacency matrices based on mutual information | |

nPresent | Number of present data entries. | |

newBlockwiseData | Create, merge and expand BlockwiseData objects | |

sizeGrWindow | Opens a graphics window with specified dimensions | |

newConsensusOptions | Create a list holding consensus calculation options. | |

orderMEs | Put close eigenvectors next to each other | |

qvalue | Estimate the q-values for a given set of p-values | |

orderMEsByHierarchicalConsensus | Order module eigengenes by their hierarchical consensus similarity | |

qvalue.restricted | qvalue convenience wrapper | |

networkScreening | Identification of genes related to a trait | |

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 | |

plotMultiHist | Plot multiple histograms in a single plot | |

replaceMissing | Replace missing values with a constant. | |

returnGeneSetsAsList | Return pre-defined gene lists in several biomedical categories. | |

plotNetworkHeatmap | Network heatmap plot | |

pruneAndMergeConsensusModules | Iterative pruning and merging of (hierarchical) consensus modules | |

sizeRestrictedClusterMerge | Cluter merging with size restrictions | |

pruneConsensusModules | Prune (hierarchical) consensus modules by removing genes with low eigengene-based intramodular connectivity | |

transposeBigData | Transpose a big matrix or data frame | |

unsignedAdjacency | Calculation of unsigned adjacency | |

prepComma | Prepend a comma to a non-empty string | |

rgcolors.func | Red and Green Color Specification | |

removeGreyME | Removes the grey eigengene from a given collection of eigengenes. | |

removePrincipalComponents | Remove leading principal components from data | |

sampledBlockwiseModules | Blockwise module identification in sampled data | |

sampledHierarchicalConsensusModules | Hierarchical consensus module identification in sampled data | |

prependZeros | Pad numbers with leading zeros to specified total width | |

simpleConsensusCalculation | Simple calculation of a single consenus | |

simpleHierarchicalConsensusCalculation | Simple hierarchical consensus calculation | |

scaleFreeFitIndex | Calculation of fitting statistics for evaluating scale free topology fit. | |

softConnectivity | Calculates connectivity of a weighted network. | |

simulateMultiExpr | Simulate multi-set expression data | |

simulateSmallLayer | Simulate small modules | |

spaste | Space-less paste | |

verboseBoxplot | Boxplot annotated by a Kruskal-Wallis p-value | |

standardColors | Colors this library uses for labeling modules. | |

randIndex | Rand index of two partitions | |

rankPvalue | Estimate the p-value for ranking consistently high (or low) on multiple lists | |

verboseIplot | Scatterplot with density | |

standardScreeningBinaryTrait | Standard screening for binatry traits | |

subsetTOM | Topological overlap for a subset of a whole set of genes | |

swapTwoBranches | Select, swap, or reflect branches in a dendrogram. | |

verboseScatterplot | Scatterplot annotated by regression line and p-value | |

setCorrelationPreservation | Summary correlation preservation measure | |

votingLinearPredictor | Voting linear predictor | |

shortenStrings | Shorten given character strings by truncating at a suitable separator. | |

signifNumeric | Round numeric columns to given significant digits. | |

signumAdjacencyFunction | Hard-thresholding adjacency function | |

standardScreeningCensoredTime | Standard Screening with regard to a Censored Time Variable | |

standardScreeningNumericTrait | Standard screening for numeric traits | |

vectorizeMatrix | Turn a matrix into a vector of non-redundant components | |

verboseBarplot | Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value | |

ImmunePathwayLists | Immune Pathways with Corresponding Gene Markers | |

No Results! |

## Last month downloads

## Details

Date | 2019-05-22 |

LinkingTo | Rcpp |

ZipData | no |

License | GPL (>= 2) |

URL | http://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/ |

NeedsCompilation | yes |

Packaged | 2019-05-22 23:44:43 UTC; plangfelder |

Repository | CRAN |

Date/Publication | 2019-05-23 05:10:03 UTC |

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

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

suggests | entropy , infotheo , minet , org.Hs.eg.db , org.Mm.eg.db |

Contributors | Steve Horvath, Peter Langfelder |

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