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WGCNA (version 1.11-2)
Weighted Gene Co-Expression Network Analysis
Description
Functions necessary to perform Weighted Gene Co-Expression Network Analysis
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Install
install.packages('WGCNA')
Monthly Downloads
18,389
Version
1.11-2
License
GPL (>= 2)
Maintainer
Peter Langfelder
Last Published
June 6th, 2011
Functions in WGCNA (1.11-2)
Search functions
accuracyMeasures
Accuracy measures for a 2x2 confusion matrix.
addTraitToMEs
Add trait information to multi-set module eigengene structure
metaZfunction
Meta-analysis Z statistic
alignExpr
Align expression data with given vector
clusterCoef
Clustering coefficient calculation
coClustering.permutationTest
Permutation test for co-clustering
fixDataStructure
Put single-set data into a form useful for multiset calculations.
BrainLists
Brain-Related Categories with Corresponding Gene Markers
GTOMdist
Generalized Topological Overlap Measure
TOMplot
Graphical representation of the Topological Overlap Matrix
adjacency
Calculate network adjacency
overlapTable
Calculate overlap of modules
TOMsimilarity
Topological overlap matrix similarity and dissimilarity
addGrid
Add grid lines to an existing plot.
coxRegressionResiduals
Deviance- and martingale residuals from a Cox regression model
blockwiseModules
Automatic network construction and module detection
mergeCloseModules
Merge close modules in gene expression data
goodSamplesMS
Filter samples with too many missing entries across multiple data sets
plotNetworkHeatmap
Network heatmap plot
coClustering
Co-clustering measure of cluster preservation between two clusterings
correlationPreservation
Preservation of eigengene correlations
bicorAndPvalue
Calculation of biweight midcorrelations and associated p-values
goodSamplesGenesMS
Iterative filtering of samples and genes with too many missing entries across multiple data sets
GOenrichmentAnalysis
Calculation of GO enrichment (experimental)
automaticNetworkScreening
One-step automatic network gene screening
greenBlackRed
Green-black-red color sequence
recutConsensusTrees
Repeat blockwise consensus module detection from pre-calculated data
consensusProjectiveKMeans
Consensus projective K-means (pre-)clustering of expression data
collapseRowsUsingKME
Selects one representative row per group based on kME
AFcorMI
Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
networkConcepts
Calculations of network concepts
goodSamples
Filter samples with too many missing entries
cutreeStaticColor
Constant height tree cut using color labels
dynamicMergeCut
Threshold for module merging
labels2colors
Convert numerical labels to colors.
corPredictionSuccess
Qunatification of success of gene screening
Inline display of progress
Inline display of progress
projectiveKMeans
Projective K-means (pre-)clustering of expression data
addGuideLines
Add vertical ``guide lines'' to a dendrogram plot
cutreeStatic
Constant-height tree cut
consensusMEDissimilarity
Consensus dissimilarity of module eigengenes.
pickHardThreshold
Analysis of scale free topology for hard-thresholding.
moduleMergeUsingKME
Merge modules and reassign genes using kME.
simulateEigengeneNetwork
Simulate eigengene network from a causal model
normalizeLabels
Transform numerical labels into normal order.
na
Basic Statistical Functions for Handling Missing Values
orderMEs
Put close eigenvectors next to each other
chooseOneHubInEachModule
Chooses a single hub gene in each module
exportNetworkToCytoscape
Export network to Cytoscape
moduleNumber
Fixed-height cut of a dendrogram.
automaticNetworkScreeningGS
One-step automatic network gene screening with external gene significance
consensusDissTOMandTree
Consensus clustering based on topological overlap and hierarchical clustering
fundamentalNetworkConcepts
Calculation of fundamental network concepts from an adjacency matrix.
checkAdjMat
Check adjacency matrix
adjacency.splineReg
Calculate network adjacency based on natural cubic spline regression
kMEcomparisonScatterplot
Function to plot kME values between two comparable data sets.
standardScreeningBinaryTrait
Standard screening for binatry traits
mutualInfoAdjacency
Calculate weighted adjacency matrices based on mutual information
relativeCorPredictionSuccess
Compare prediction success
networkScreeningGS
Network gene screening with an external gene significance measure
WGCNA-package
Weighted Gene Co-Expression Network Analysis
removePrincipalComponents
Remove leading principal components from data
corPvalueStudent
Student asymptotic p-value for correlation
corPvalueFisher
Fisher's asymptotic p-value for correlation
redWhiteGreen
Red-white-green color sequence
bicor
Biweight Midcorrelation
checkSets
Check structure and retrieve sizes of a group of datasets.
exportNetworkToVisANT
Export network data in format readable by VisANT
blockwiseConsensusModules
Find consensus modules across several datasets.
colQuantileC
Fast colunm-wise quantile of a matrix.
simulateMultiExpr
Simulate multi-set expression data
greenWhiteRed
Green-white-red color sequence
plot.mat
Red and Green Color Image of Data Matrix
conformityDecomposition
Conformity and module based decomposition of a network adjacency matrix.
plotMEpairs
Pairwise scatterplots of eigengenes
plotDendroAndColors
Dendrogram plot with color annotation of objects
keepCommonProbes
Keep probes that are shared among given data sets
hubGeneSignificance
Hubgene significance
matrixToNetwork
Construct a network from a matrix
labeledBarplot
Barplot with text or color labels.
nearestNeighborConnectivity
Connectivity to a constant number of nearest neighbors
chooseTopHubInEachModule
Chooses the top hub gene in each module
goodSamplesGenes
Iterative filtering of samples and genes with too many missing entries
modulePreservation
Calculation of module preservation statistics
collectGarbage
Iterative garbage collection.
pquantile
Parallel quantile, median, mean
rankPvalue
Estimate the p-value for ranking consistently high (or low) on multiple lists
nearestCentroidPredictor
Nearest centroid predictor
collapseRows
Select one representative row per group
displayColors
Show colors used to label modules
goodGenes
Filter genes with too many missing entries
populationMeansInAdmixture
Estimate the population-specific mean values in an admixed population.
plotClusterTreeSamples
Annotated clustering dendrogram of microarray samples
proportionsInAdmixture
Estimate the proportion of pure populations in an admixed population based on marker expression values.
plotModuleSignificance
Barplot of module significance
intramodularConnectivity
Calculation of intramodular connectivity
simulateDatExpr5Modules
Simplified simulation of expression data
scaleFreeFitIndex
Calculation of fitting statistics for evaluating scale free topology fit.
plotColorUnderTree
Plot color rows under a dendrogram
recutBlockwiseTrees
Repeat blockwise module detection from pre-calculated data
labeledHeatmap
Produce a labeled heatmap plot
nearestNeighborConnectivityMS
Connectivity to a constant number of nearest neighbors across multiple data sets
networkScreening
Identification of genes related to a trait
stat.diag.da
Diagonal Discriminant Analysis
corAndPvalue
Calculation of correlations and associated p-values
rgcolors.func
Red and Green Color Specification
randIndex
Rand index of two partitions
cor
Fast calculations of Pearson correlation.
signedKME
Signed eigengene-based connectivity
goodGenesMS
Filter genes with too many missing entries across multiple sets
numbers2colors
Color representation for a numeric variable
nPresent
Number of present data entries.
simulateModule
Simulate a gene co-expression module
orderBranchesUsingHubGenes
Optimize dendrogram using branch swaps and reflections.
simulateDatExpr
Simulation of expression data
signumAdjacencyFunction
Hard-thresholding adjacency function
plot.cor
Red and Green Color Image of Correlation Matrix
spaste
Space-less paste
prepComma
Prepend a comma to a non-empty string
preservationNetworkConnectivity
Network preservation calculations
sizeGrWindow
Opens a graphics window with specified dimensions
qvalue
Estimate the q-values for a given set of p-values
moduleColor.getMEprefix
Get the prefix used to label module eigengenes.
setCorrelationPreservation
Summary correlation preservation measure
matchLabels
Relabel module labels to best match the given reference labels
plotEigengeneNetworks
Eigengene network plot
sigmoidAdjacencyFunction
Sigmoid-type adacency function.
standardScreeningNumericTrait
Standard screening for numeric traits
votingLinearPredictor
Voting linear predictor
stdErr
Standard error of the mean of a given vector.
stratifiedBarplot
Bar plots of data across two splitting parameters
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
vectorizeMatrix
Turn a matrix into a vector of non-redundant components
standardScreeningCensoredTime
Standard Screening with regard to a Censored Time Variable
verboseScatterplot
Scatterplot annotated by regression line and p-value
subsetTOM
Topological overlap for a subset of a whole set of genes
stat.bwss
Between and Within Group Sum of Squares Calculation
scaleFreePlot
Visual check of scale-free topology
verboseBoxplot
Boxplot annotated by a Kruskal-Wallis p-value
standardColors
Colors this library uses for labeling modules.
removeGreyME
Removes the grey eigengene from a given collection of eigengenes.
unsignedAdjacency
Calculation of unsigned adjacency
userListEnrichment
Measure enrichment between inputted and user-defined lists
conformityBasedNetworkConcepts
Calculation of conformity-based network concepts.
labelPoints
Label scatterplot points
BloodLists
Blood Cell Types with Corresponding Gene Markers
TOMsimilarityFromExpr
Topological overlap matrix
addErrorBars
Add error bars to a barplot.
adjacency.polyReg
Adjacency matrix based on polynomial regression
consensusOrderMEs
Put close eigenvectors next to each other in several sets.
moduleEigengenes
Calculate module eigengenes.
multiSetMEs
Calculate module eigengenes.
overlapTableUsingKME
Determines significant overlap between modules in two networks based on kME tables.
pickSoftThreshold
Analysis of scale free topology for soft-thresholding
propVarExplained
Proportion of variance explained by eigengenes.
softConnectivity
Calculates connectivity of a weighted network.
swapTwoBranches
Select, swap, or reflect branches in a dendrogram.
simulateSmallLayer
Simulate small modules