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WGCNA (version 1.26)
Weighted Correlation Network Analysis
Description
Functions necessary to perform Weighted Correlation Network Analysis.
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Install
install.packages('WGCNA')
Monthly Downloads
18,389
Version
1.26
License
GPL (>= 2)
Maintainer
Peter Langfelder
Last Published
March 7th, 2013
Functions in WGCNA (1.26)
Search functions
TOMplot
Graphical representation of the Topological Overlap Matrix
metaZfunction
Meta-analysis Z statistic
SCsLists
Stem Cell-Related Genes with Corresponding Gene Markers
consensusKME
Calculate consensus kME (eigengene-based connectivities) across multiple data sets.
blockwiseConsensusModules
Find consensus modules across several datasets.
TOMsimilarityFromExpr
Topological overlap matrix
displayColors
Show colors used to label modules
collectGarbage
Iterative garbage collection.
goodSamples
Filter samples with too many missing entries
corPredictionSuccess
Qunatification of success of gene screening
fixDataStructure
Put single-set data into a form useful for multiset calculations.
removeGreyME
Removes the grey eigengene from a given collection of eigengenes.
signumAdjacencyFunction
Hard-thresholding adjacency function
rankPvalue
Estimate the p-value for ranking consistently high (or low) on multiple lists
labelPoints
Label scatterplot points
scaleFreeFitIndex
Calculation of fitting statistics for evaluating scale free topology fit.
cor
Fast calculations of Pearson correlation.
WGCNA-package
Weighted Gene Co-Expression Network Analysis
setCorrelationPreservation
Summary correlation preservation measure
corPvalueFisher
Fisher's asymptotic p-value for correlation
pquantile
Parallel quantile, median, mean
goodGenesMS
Filter genes with too many missing entries across multiple sets
orderBranchesUsingHubGenes
Optimize dendrogram using branch swaps and reflections.
coxRegressionResiduals
Deviance- and martingale residuals from a Cox regression model
matchLabels
Relabel module labels to best match the given reference labels
standardScreeningNumericTrait
Standard screening for numeric traits
corAndPvalue
Calculation of correlations and associated p-values
blockwiseIndividualTOMs
Calculation of block-wise topological overlaps
greenBlackRed
Green-black-red color sequence
kMEcomparisonScatterplot
Function to plot kME values between two comparable data sets.
dynamicMergeCut
Threshold for module merging
addGrid
Add grid lines to an existing plot.
AFcorMI
Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
automaticNetworkScreeningGS
One-step automatic network gene screening with external gene significance
blockwiseModules
Automatic network construction and module detection
accuracyMeasures
Accuracy measures for a 2x2 confusion matrix or for vectors of predicted and observed values.
bicor
Biweight Midcorrelation
adjacency
Calculate network adjacency
intramodularConnectivity
Calculation of intramodular connectivity
removePrincipalComponents
Remove leading principal components from data
verboseBoxplot
Boxplot annotated by a Kruskal-Wallis p-value
metaAnalysis
Meta-analysis of binary and continuous variables
chooseTopHubInEachModule
Chooses the top hub gene in each module
nearestNeighborConnectivity
Connectivity to a constant number of nearest neighbors
modulePreservation
Calculation of module preservation statistics
coClustering.permutationTest
Permutation test for co-clustering
adjacency.polyReg
Adjacency matrix based on polynomial regression
colQuantileC
Fast colunm-wise quantile of a matrix.
moduleEigengenes
Calculate module eigengenes.
collapseRowsUsingKME
Selects one representative row per group based on kME
mutualInfoAdjacency
Calculate weighted adjacency matrices based on mutual information
populationMeansInAdmixture
Estimate the population-specific mean values in an admixed population.
pickHardThreshold
Analysis of scale free topology for hard-thresholding.
multiData.eigengeneSignificance
Eigengene significance across multiple sets
networkScreeningGS
Network gene screening with an external gene significance measure
greenWhiteRed
Green-white-red color sequence
qvalue.restricted
qvalue convenience wrapper
moduleColor.getMEprefix
Get the prefix used to label module eigengenes.
clusterCoef
Clustering coefficient calculation
simulateSmallLayer
Simulate small modules
stat.bwss
Between and Within Group Sum of Squares Calculation
checkSets
Check structure and retrieve sizes of a group of datasets.
networkScreening
Identification of genes related to a trait
goodSamplesGenes
Iterative filtering of samples and genes with too many missing entries
normalizeLabels
Transform numerical labels into normal order.
sizeGrWindow
Opens a graphics window with specified dimensions
simulateModule
Simulate a gene co-expression module
hubGeneSignificance
Hubgene significance
plotDendroAndColors
Dendrogram plot with color annotation of objects
plotEigengeneNetworks
Eigengene network plot
swapTwoBranches
Select, swap, or reflect branches in a dendrogram.
consensusMEDissimilarity
Consensus dissimilarity of module eigengenes.
moduleNumber
Fixed-height cut of a dendrogram.
goodSamplesMS
Filter samples with too many missing entries across multiple data sets
nSets
Number of sets in a multi-set variable
labels2colors
Convert numerical labels to colors.
prepComma
Prepend a comma to a non-empty string
softConnectivity
Calculates connectivity of a weighted network.
recutConsensusTrees
Repeat blockwise consensus module detection from pre-calculated data
orderMEs
Put close eigenvectors next to each other
redWhiteGreen
Red-white-green color sequence
stat.diag.da
Diagonal Discriminant Analysis
addGuideLines
Add vertical ``guide lines'' to a dendrogram plot
nearestNeighborConnectivityMS
Connectivity to a constant number of nearest neighbors across multiple data sets
plotCor
Red and Green Color Image of Correlation Matrix
plotMEpairs
Pairwise scatterplots of eigengenes
propVarExplained
Proportion of variance explained by eigengenes.
preservationNetworkConnectivity
Network preservation calculations
lowerTri2matrix
Reconstruct a symmetric matrix from a distance (lower-triangular) representation
GOenrichmentAnalysis
Calculation of GO enrichment (experimental)
verboseIplot
Scatterplot with density
blockSize
Attempt to calculate an appropriate block size to maximize efficiency of block-wise calcualtions.
simulateDatExpr5Modules
Simplified simulation of expression data
BrainRegionMarkers
Gene Markers for Regions of the Human Brain
cutreeStatic
Constant-height tree cut
overlapTable
Calculate overlap of modules
plotNetworkHeatmap
Network heatmap plot
vectorizeMatrix
Turn a matrix into a vector of non-redundant components
goodSamplesGenesMS
Iterative filtering of samples and genes with too many missing entries across multiple data sets
labeledHeatmap
Produce a labeled heatmap plot
randomGLMpredictor
Random generalized linear model predictor
GTOMdist
Generalized Topological Overlap Measure
verboseScatterplot
Scatterplot annotated by regression line and p-value
relativeCorPredictionSuccess
Compare prediction success
goodGenes
Filter genes with too many missing entries
plotMat
Red and Green Color Image of Data Matrix
conformityDecomposition
Conformity and module based decomposition of a network adjacency matrix.
transposeBigData
Transpose a big matrix or data frame
rgcolors.func
Red and Green Color Specification
votingLinearPredictor
Voting linear predictor
na
Basic Statistical Functions for Handling Missing Values
randIndex
Rand index of two partitions
nPresent
Number of present data entries.
recutBlockwiseTrees
Repeat blockwise module detection from pre-calculated data
stratifiedBarplot
Bar plots of data across two splitting parameters
plotClusterTreeSamples
Annotated clustering dendrogram of microarray samples
simulateEigengeneNetwork
Simulate eigengene network from a causal model
BrainLists
Brain-Related Categories with Corresponding Gene Markers
userListEnrichment
Measure enrichment between inputted and user-defined lists
addErrorBars
Add error bars to a barplot.
spaste
Space-less paste
allocateJobs
Divide tasks among workers
coClustering
Co-clustering measure of cluster preservation between two clusterings
corPvalueStudent
Student asymptotic p-value for correlation
ImmunePathwayLists
Immune Pathways with Corresponding Gene Markers
alignExpr
Align expression data with given vector
automaticNetworkScreening
One-step automatic network gene screening
matrixToNetwork
Construct a network from a matrix
TrueTrait
Estimate the true trait underlying a list of surrogate markers.
adjacency.splineReg
Calculate network adjacency based on natural cubic spline regression
bicorAndPvalue
Calculation of biweight midcorrelations and associated p-values
mergeCloseModules
Merge close modules in gene expression data
chooseOneHubInEachModule
Chooses a single hub gene in each module
TOMsimilarity
Topological overlap matrix similarity and dissimilarity
fundamentalNetworkConcepts
Calculation of fundamental network concepts from an adjacency matrix.
checkAdjMat
Check adjacency matrix
nearestCentroidPredictor
Nearest centroid predictor
stdErr
Standard error of the mean of a given vector.
proportionsInAdmixture
Estimate the proportion of pure populations in an admixed population based on marker expression values.
allowWGCNAThreads
Allow and disable multi-threading for certain WGCNA calculations
BloodLists
Blood Cell Types with Corresponding Gene Markers
moduleMergeUsingKME
Merge modules and reassign genes using kME.
numbers2colors
Color representation for a numeric variable
networkConcepts
Calculations of network concepts
scaleFreePlot
Visual check of scale-free topology
signedKME
Signed eigengene-based connectivity
sigmoidAdjacencyFunction
Sigmoid-type adacency function.
consensusDissTOMandTree
Consensus clustering based on topological overlap and hierarchical clustering
simulateDatExpr
Simulation of expression data
standardColors
Colors this library uses for labeling modules.
correlationPreservation
Preservation of eigengene correlations
cutreeStaticColor
Constant height tree cut using color labels
unsignedAdjacency
Calculation of unsigned adjacency
verboseBarplot
Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
conformityBasedNetworkConcepts
Calculation of conformity-based network concepts.
multiSetMEs
Calculate module eigengenes.
standardScreeningCensoredTime
Standard Screening with regard to a Censored Time Variable
projectiveKMeans
Projective K-means (pre-)clustering of expression data
subsetTOM
Topological overlap for a subset of a whole set of genes
addTraitToMEs
Add trait information to multi-set module eigengene structure
labeledBarplot
Barplot with text or color labels.
overlapTableUsingKME
Determines significant overlap between modules in two networks based on kME tables.
plotColorUnderTree
Plot color rows under a dendrogram
qvalue
Estimate the q-values for a given set of p-values
Inline display of progress
Inline display of progress
simulateMultiExpr
Simulate multi-set expression data
returnGeneSetsAsList
Return pre-defined gene lists in several biomedical categories.
blueWhiteRed
Blue-white-red color sequence
collapseRows
Select one representative row per group
consensusProjectiveKMeans
Consensus projective K-means (pre-)clustering of expression data
consensusOrderMEs
Put close eigenvectors next to each other in several sets.
exportNetworkToVisANT
Export network data in format readable by VisANT
keepCommonProbes
Keep probes that are shared among given data sets
pickSoftThreshold
Analysis of scale free topology for soft-thresholding
plotModuleSignificance
Barplot of module significance
standardScreeningBinaryTrait
Standard screening for binatry traits
vectorTOM
Topological overlap for a subset of the whole set of genes
exportNetworkToCytoscape
Export network to Cytoscape