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WGCNA (version 1.13)
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
1.13
License
GPL (>= 2)
Maintainer
Peter Langfelder
Last Published
August 18th, 2011
Functions in WGCNA (1.13)
Search functions
keepCommonProbes
Keep probes that are shared among given data sets
coxRegressionResiduals
Deviance- and martingale residuals from a Cox regression model
BrainLists
Brain-Related Categories with Corresponding Gene Markers
BloodLists
Blood Cell Types with Corresponding Gene Markers
GOenrichmentAnalysis
Calculation of GO enrichment (experimental)
alignExpr
Align expression data with given vector
chooseTopHubInEachModule
Chooses the top hub gene in each module
collapseRows
Select one representative row per group
intramodularConnectivity
Calculation of intramodular connectivity
nearestNeighborConnectivity
Connectivity to a constant number of nearest neighbors
collapseRowsUsingKME
Selects one representative row per group based on kME
networkConcepts
Calculations of network concepts
consensusOrderMEs
Put close eigenvectors next to each other in several sets.
matchLabels
Relabel module labels to best match the given reference labels
allowWGCNAThreads
Allow and disable multi-threading for certain WGCNA calculations
numbers2colors
Color representation for a numeric variable
goodGenes
Filter genes with too many missing entries
metaZfunction
Meta-analysis Z statistic
signedKME
Signed eigengene-based connectivity
correlationPreservation
Preservation of eigengene correlations
signumAdjacencyFunction
Hard-thresholding adjacency function
overlapTableUsingKME
Determines significant overlap between modules in two networks based on kME tables.
corAndPvalue
Calculation of correlations and associated p-values
plotModuleSignificance
Barplot of module significance
checkSets
Check structure and retrieve sizes of a group of datasets.
pickSoftThreshold
Analysis of scale free topology for soft-thresholding
plotNetworkHeatmap
Network heatmap plot
sizeGrWindow
Opens a graphics window with specified dimensions
mutualInfoAdjacency
Calculate weighted adjacency matrices based on mutual information
adjacency
Calculate network adjacency
stdErr
Standard error of the mean of a given vector.
nPresent
Number of present data entries.
blockwiseModules
Automatic network construction and module detection
coClustering
Co-clustering measure of cluster preservation between two clusterings
plotColorUnderTree
Plot color rows under a dendrogram
colQuantileC
Fast colunm-wise quantile of a matrix.
addErrorBars
Add error bars to a barplot.
stat.diag.da
Diagonal Discriminant Analysis
cor
Fast calculations of Pearson correlation.
recutBlockwiseTrees
Repeat blockwise module detection from pre-calculated data
TOMplot
Graphical representation of the Topological Overlap Matrix
simulateEigengeneNetwork
Simulate eigengene network from a causal model
accuracyMeasures
Accuracy measures for a 2x2 confusion matrix.
bicorAndPvalue
Calculation of biweight midcorrelations and associated p-values
addGuideLines
Add vertical ``guide lines'' to a dendrogram plot
addGrid
Add grid lines to an existing plot.
fixDataStructure
Put single-set data into a form useful for multiset calculations.
displayColors
Show colors used to label modules
verboseBarplot
Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
nearestCentroidPredictor
Nearest centroid predictor
TOMsimilarity
Topological overlap matrix similarity and dissimilarity
goodSamplesMS
Filter samples with too many missing entries across multiple data sets
TOMsimilarityFromExpr
Topological overlap matrix
addTraitToMEs
Add trait information to multi-set module eigengene structure
prepComma
Prepend a comma to a non-empty string
chooseOneHubInEachModule
Chooses a single hub gene in each module
hubGeneSignificance
Hubgene significance
plotEigengeneNetworks
Eigengene network plot
cutreeStatic
Constant-height tree cut
nearestNeighborConnectivityMS
Connectivity to a constant number of nearest neighbors across multiple data sets
automaticNetworkScreeningGS
One-step automatic network gene screening with external gene significance
conformityDecomposition
Conformity and module based decomposition of a network adjacency matrix.
conformityBasedNetworkConcepts
Calculation of conformity-based network concepts.
kMEcomparisonScatterplot
Function to plot kME values between two comparable data sets.
Inline display of progress
Inline display of progress
randIndex
Rand index of two partitions
bicor
Biweight Midcorrelation
greenWhiteRed
Green-white-red color sequence
pquantile
Parallel quantile, median, mean
labeledBarplot
Barplot with text or color labels.
standardScreeningNumericTrait
Standard screening for numeric traits
plotCor
Red and Green Color Image of Correlation Matrix
qvalue
Estimate the q-values for a given set of p-values
swapTwoBranches
Select, swap, or reflect branches in a dendrogram.
modulePreservation
Calculation of module preservation statistics
coClustering.permutationTest
Permutation test for co-clustering
preservationNetworkConnectivity
Network preservation calculations
moduleMergeUsingKME
Merge modules and reassign genes using kME.
projectiveKMeans
Projective K-means (pre-)clustering of expression data
consensusMEDissimilarity
Consensus dissimilarity of module eigengenes.
mergeCloseModules
Merge close modules in gene expression data
relativeCorPredictionSuccess
Compare prediction success
adjacency.splineReg
Calculate network adjacency based on natural cubic spline regression
spaste
Space-less paste
dynamicMergeCut
Threshold for module merging
fundamentalNetworkConcepts
Calculation of fundamental network concepts from an adjacency matrix.
cutreeStaticColor
Constant height tree cut using color labels
labelPoints
Label scatterplot points
sigmoidAdjacencyFunction
Sigmoid-type adacency function.
scaleFreeFitIndex
Calculation of fitting statistics for evaluating scale free topology fit.
exportNetworkToCytoscape
Export network to Cytoscape
verboseScatterplot
Scatterplot annotated by regression line and p-value
standardScreeningBinaryTrait
Standard screening for binatry traits
overlapTable
Calculate overlap of modules
userListEnrichment
Measure enrichment between inputted and user-defined lists
multiSetMEs
Calculate module eigengenes.
checkAdjMat
Check adjacency matrix
blockwiseConsensusModules
Find consensus modules across several datasets.
rankPvalue
Estimate the p-value for ranking consistently high (or low) on multiple lists
WGCNA-package
Weighted Gene Co-Expression Network Analysis
orderBranchesUsingHubGenes
Optimize dendrogram using branch swaps and reflections.
collectGarbage
Iterative garbage collection.
goodSamplesGenes
Iterative filtering of samples and genes with too many missing entries
plotMEpairs
Pairwise scatterplots of eigengenes
removeGreyME
Removes the grey eigengene from a given collection of eigengenes.
setCorrelationPreservation
Summary correlation preservation measure
goodSamples
Filter samples with too many missing entries
labeledHeatmap
Produce a labeled heatmap plot
greenBlackRed
Green-black-red color sequence
redWhiteGreen
Red-white-green color sequence
propVarExplained
Proportion of variance explained by eigengenes.
votingLinearPredictor
Voting linear predictor
scaleFreePlot
Visual check of scale-free topology
pickHardThreshold
Analysis of scale free topology for hard-thresholding.
moduleNumber
Fixed-height cut of a dendrogram.
consensusProjectiveKMeans
Consensus projective K-means (pre-)clustering of expression data
matrixToNetwork
Construct a network from a matrix
removePrincipalComponents
Remove leading principal components from data
proportionsInAdmixture
Estimate the proportion of pure populations in an admixed population based on marker expression values.
stratifiedBarplot
Bar plots of data across two splitting parameters
subsetTOM
Topological overlap for a subset of a whole set of genes
GTOMdist
Generalized Topological Overlap Measure
networkScreening
Identification of genes related to a trait
simulateModule
Simulate a gene co-expression module
populationMeansInAdmixture
Estimate the population-specific mean values in an admixed population.
orderMEs
Put close eigenvectors next to each other
verboseBoxplot
Boxplot annotated by a Kruskal-Wallis p-value
simulateMultiExpr
Simulate multi-set expression data
moduleEigengenes
Calculate module eigengenes.
normalizeLabels
Transform numerical labels into normal order.
corPredictionSuccess
Qunatification of success of gene screening
simulateDatExpr
Simulation of expression data
consensusDissTOMandTree
Consensus clustering based on topological overlap and hierarchical clustering
unsignedAdjacency
Calculation of unsigned adjacency
goodSamplesGenesMS
Iterative filtering of samples and genes with too many missing entries across multiple data sets
labels2colors
Convert numerical labels to colors.
na
Basic Statistical Functions for Handling Missing Values
networkScreeningGS
Network gene screening with an external gene significance measure
plotClusterTreeSamples
Annotated clustering dendrogram of microarray samples
clusterCoef
Clustering coefficient calculation
adjacency.polyReg
Adjacency matrix based on polynomial regression
plotMat
Red and Green Color Image of Data Matrix
simulateSmallLayer
Simulate small modules
standardScreeningCensoredTime
Standard Screening with regard to a Censored Time Variable
plotDendroAndColors
Dendrogram plot with color annotation of objects
recutConsensusTrees
Repeat blockwise consensus module detection from pre-calculated data
AFcorMI
Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
corPvalueStudent
Student asymptotic p-value for correlation
exportNetworkToVisANT
Export network data in format readable by VisANT
goodGenesMS
Filter genes with too many missing entries across multiple sets
moduleColor.getMEprefix
Get the prefix used to label module eigengenes.
rgcolors.func
Red and Green Color Specification
simulateDatExpr5Modules
Simplified simulation of expression data
vectorizeMatrix
Turn a matrix into a vector of non-redundant components
corPvalueFisher
Fisher's asymptotic p-value for correlation
automaticNetworkScreening
One-step automatic network gene screening
standardColors
Colors this library uses for labeling modules.
softConnectivity
Calculates connectivity of a weighted network.
stat.bwss
Between and Within Group Sum of Squares Calculation
vectorTOM
Topological overlap for a subset of the whole set of genes