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WGCNA (version 1.17)
Weighted Correlation Network Analysis
Description
Functions necessary to perform Weighted Correlation Network Analysis
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Install
install.packages('WGCNA')
Monthly Downloads
11,522
Version
1.17
License
GPL (>= 2)
Maintainer
Peter Langfelder
Last Published
December 7th, 2011
Functions in WGCNA (1.17)
Search functions
BrainLists
Brain-Related Categories with Corresponding Gene Markers
TOMsimilarity
Topological overlap matrix similarity and dissimilarity
cutreeStaticColor
Constant height tree cut using color labels
standardScreeningCensoredTime
Standard Screening with regard to a Censored Time Variable
coxRegressionResiduals
Deviance- and martingale residuals from a Cox regression model
hubGeneSignificance
Hubgene significance
alignExpr
Align expression data with given vector
redWhiteGreen
Red-white-green color sequence
modulePreservation
Calculation of module preservation statistics
consensusOrderMEs
Put close eigenvectors next to each other in several sets.
mergeCloseModules
Merge close modules in gene expression data
adjacency
Calculate network adjacency
greenWhiteRed
Green-white-red color sequence
nearestNeighborConnectivity
Connectivity to a constant number of nearest neighbors
unsignedAdjacency
Calculation of unsigned adjacency
prepComma
Prepend a comma to a non-empty string
propVarExplained
Proportion of variance explained by eigengenes.
scaleFreeFitIndex
Calculation of fitting statistics for evaluating scale free topology fit.
cutreeStatic
Constant-height tree cut
simulateEigengeneNetwork
Simulate eigengene network from a causal model
collapseRows
Select one representative row per group
projectiveKMeans
Projective K-means (pre-)clustering of expression data
WGCNA-package
Weighted Gene Co-Expression Network Analysis
chooseOneHubInEachModule
Chooses a single hub gene in each module
verboseBoxplot
Boxplot annotated by a Kruskal-Wallis p-value
blockwiseModules
Automatic network construction and module detection
verboseBarplot
Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
consensusProjectiveKMeans
Consensus projective K-means (pre-)clustering of expression data
consensusDissTOMandTree
Consensus clustering based on topological overlap and hierarchical clustering
plotCor
Red and Green Color Image of Correlation Matrix
SCsLists
Stem Cell-Related Genes with Corresponding Gene Markers
vectorTOM
Topological overlap for a subset of the whole set of genes
networkScreening
Identification of genes related to a trait
addGrid
Add grid lines to an existing plot.
coClustering
Co-clustering measure of cluster preservation between two clusterings
qvalue
Estimate the q-values for a given set of p-values
orderMEs
Put close eigenvectors next to each other
addErrorBars
Add error bars to a barplot.
goodGenes
Filter genes with too many missing entries
corPvalueFisher
Fisher's asymptotic p-value for correlation
AFcorMI
Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
GOenrichmentAnalysis
Calculation of GO enrichment (experimental)
goodSamples
Filter samples with too many missing entries
verboseIplot
Scatterplot with density
checkSets
Check structure and retrieve sizes of a group of datasets.
mutualInfoAdjacency
Calculate weighted adjacency matrices based on mutual information
plotModuleSignificance
Barplot of module significance
setCorrelationPreservation
Summary correlation preservation measure
simulateModule
Simulate a gene co-expression module
consensusKME
Calculate consensus kME (eigengene-based connectivities) across multiple data sets.
automaticNetworkScreeningGS
One-step automatic network gene screening with external gene significance
bicor
Biweight Midcorrelation
goodSamplesGenes
Iterative filtering of samples and genes with too many missing entries
kMEcomparisonScatterplot
Function to plot kME values between two comparable data sets.
recutBlockwiseTrees
Repeat blockwise module detection from pre-calculated data
labeledBarplot
Barplot with text or color labels.
exportNetworkToVisANT
Export network data in format readable by VisANT
blockwiseConsensusModules
Find consensus modules across several datasets.
greenBlackRed
Green-black-red color sequence
TOMplot
Graphical representation of the Topological Overlap Matrix
allowWGCNAThreads
Allow and disable multi-threading for certain WGCNA calculations
nearestCentroidPredictor
Nearest centroid predictor
removeGreyME
Removes the grey eigengene from a given collection of eigengenes.
metaAnalysis
Meta-analysis of binary and continuous variables
cor
Fast calculations of Pearson correlation.
Inline display of progress
Inline display of progress
matrixToNetwork
Construct a network from a matrix
plotClusterTreeSamples
Annotated clustering dendrogram of microarray samples
moduleNumber
Fixed-height cut of a dendrogram.
overlapTable
Calculate overlap of modules
collapseRowsUsingKME
Selects one representative row per group based on kME
checkAdjMat
Check adjacency matrix
BloodLists
Blood Cell Types with Corresponding Gene Markers
bicorAndPvalue
Calculation of biweight midcorrelations and associated p-values
intramodularConnectivity
Calculation of intramodular connectivity
correlationPreservation
Preservation of eigengene correlations
corPredictionSuccess
Qunatification of success of gene screening
moduleMergeUsingKME
Merge modules and reassign genes using kME.
scaleFreePlot
Visual check of scale-free topology
consensusMEDissimilarity
Consensus dissimilarity of module eigengenes.
plotColorUnderTree
Plot color rows under a dendrogram
adjacency.splineReg
Calculate network adjacency based on natural cubic spline regression
displayColors
Show colors used to label modules
TOMsimilarityFromExpr
Topological overlap matrix
colQuantileC
Fast colunm-wise quantile of a matrix.
simulateSmallLayer
Simulate small modules
labels2colors
Convert numerical labels to colors.
dynamicMergeCut
Threshold for module merging
coClustering.permutationTest
Permutation test for co-clustering
automaticNetworkScreening
One-step automatic network gene screening
signumAdjacencyFunction
Hard-thresholding adjacency function
networkConcepts
Calculations of network concepts
moduleColor.getMEprefix
Get the prefix used to label module eigengenes.
plotMat
Red and Green Color Image of Data Matrix
exportNetworkToCytoscape
Export network to Cytoscape
stratifiedBarplot
Bar plots of data across two splitting parameters
labeledHeatmap
Produce a labeled heatmap plot
goodGenesMS
Filter genes with too many missing entries across multiple sets
simulateDatExpr
Simulation of expression data
plotDendroAndColors
Dendrogram plot with color annotation of objects
nPresent
Number of present data entries.
networkScreeningGS
Network gene screening with an external gene significance measure
moduleEigengenes
Calculate module eigengenes.
preservationNetworkConnectivity
Network preservation calculations
numbers2colors
Color representation for a numeric variable
standardScreeningBinaryTrait
Standard screening for binatry traits
goodSamplesMS
Filter samples with too many missing entries across multiple data sets
signedKME
Signed eigengene-based connectivity
multiSetMEs
Calculate module eigengenes.
recutConsensusTrees
Repeat blockwise consensus module detection from pre-calculated data
rankPvalue
Estimate the p-value for ranking consistently high (or low) on multiple lists
sizeGrWindow
Opens a graphics window with specified dimensions
fundamentalNetworkConcepts
Calculation of fundamental network concepts from an adjacency matrix.
randIndex
Rand index of two partitions
simulateMultiExpr
Simulate multi-set expression data
stat.diag.da
Diagonal Discriminant Analysis
userListEnrichment
Measure enrichment between inputted and user-defined lists
verboseScatterplot
Scatterplot annotated by regression line and p-value
relativeCorPredictionSuccess
Compare prediction success
overlapTableUsingKME
Determines significant overlap between modules in two networks based on kME tables.
goodSamplesGenesMS
Iterative filtering of samples and genes with too many missing entries across multiple data sets
keepCommonProbes
Keep probes that are shared among given data sets
plotMEpairs
Pairwise scatterplots of eigengenes
softConnectivity
Calculates connectivity of a weighted network.
clusterCoef
Clustering coefficient calculation
matchLabels
Relabel module labels to best match the given reference labels
votingLinearPredictor
Voting linear predictor
sigmoidAdjacencyFunction
Sigmoid-type adacency function.
standardScreeningNumericTrait
Standard screening for numeric traits
proportionsInAdmixture
Estimate the proportion of pure populations in an admixed population based on marker expression values.
spaste
Space-less paste
metaZfunction
Meta-analysis Z statistic
orderBranchesUsingHubGenes
Optimize dendrogram using branch swaps and reflections.
na
Basic Statistical Functions for Handling Missing Values
standardColors
Colors this library uses for labeling modules.
addTraitToMEs
Add trait information to multi-set module eigengene structure
adjacency.polyReg
Adjacency matrix based on polynomial regression
addGuideLines
Add vertical ``guide lines'' to a dendrogram plot
corAndPvalue
Calculation of correlations and associated p-values
conformityBasedNetworkConcepts
Calculation of conformity-based network concepts.
corPvalueStudent
Student asymptotic p-value for correlation
populationMeansInAdmixture
Estimate the population-specific mean values in an admixed population.
collectGarbage
Iterative garbage collection.
pickSoftThreshold
Analysis of scale free topology for soft-thresholding
plotEigengeneNetworks
Eigengene network plot
nearestNeighborConnectivityMS
Connectivity to a constant number of nearest neighbors across multiple data sets
subsetTOM
Topological overlap for a subset of a whole set of genes
stdErr
Standard error of the mean of a given vector.
plotNetworkHeatmap
Network heatmap plot
normalizeLabels
Transform numerical labels into normal order.
swapTwoBranches
Select, swap, or reflect branches in a dendrogram.
removePrincipalComponents
Remove leading principal components from data
qvalue.restricted
qvalue convenience wrapper
GTOMdist
Generalized Topological Overlap Measure
accuracyMeasures
Accuracy measures for a 2x2 confusion matrix.
chooseTopHubInEachModule
Chooses the top hub gene in each module
pickHardThreshold
Analysis of scale free topology for hard-thresholding.
rgcolors.func
Red and Green Color Specification
simulateDatExpr5Modules
Simplified simulation of expression data
vectorizeMatrix
Turn a matrix into a vector of non-redundant components
fixDataStructure
Put single-set data into a form useful for multiset calculations.
labelPoints
Label scatterplot points
multiData.eigengeneSignificance
Eigengene significance across multiple sets
conformityDecomposition
Conformity and module based decomposition of a network adjacency matrix.
pquantile
Parallel quantile, median, mean
stat.bwss
Between and Within Group Sum of Squares Calculation