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WGCNA (version 1.14)
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
1.14
License
GPL (>= 2)
Maintainer
Peter Langfelder
Last Published
November 10th, 2011
Functions in WGCNA (1.14)
Search functions
allowWGCNAThreads
Allow and disable multi-threading for certain WGCNA calculations
SCsLists
Stem Cell-Related Genes with Corresponding Gene Markers
blockwiseConsensusModules
Find consensus modules across several datasets.
goodSamplesMS
Filter samples with too many missing entries across multiple data sets
moduleEigengenes
Calculate module eigengenes.
nPresent
Number of present data entries.
qvalue.restricted
qvalue convenience wrapper
preservationNetworkConnectivity
Network preservation calculations
checkSets
Check structure and retrieve sizes of a group of datasets.
addGuideLines
Add vertical ``guide lines'' to a dendrogram plot
cutreeStatic
Constant-height tree cut
BrainLists
Brain-Related Categories with Corresponding Gene Markers
adjacency.polyReg
Adjacency matrix based on polynomial regression
matrixToNetwork
Construct a network from a matrix
consensusOrderMEs
Put close eigenvectors next to each other in several sets.
BloodLists
Blood Cell Types with Corresponding Gene Markers
networkScreeningGS
Network gene screening with an external gene significance measure
corAndPvalue
Calculation of correlations and associated p-values
modulePreservation
Calculation of module preservation statistics
clusterCoef
Clustering coefficient calculation
bicor
Biweight Midcorrelation
plotCor
Red and Green Color Image of Correlation Matrix
coClustering
Co-clustering measure of cluster preservation between two clusterings
AFcorMI
Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
goodSamples
Filter samples with too many missing entries
displayColors
Show colors used to label modules
WGCNA-package
Weighted Gene Co-Expression Network Analysis
plotModuleSignificance
Barplot of module significance
swapTwoBranches
Select, swap, or reflect branches in a dendrogram.
consensusKME
Calculate consensus kME (eigengene-based connectivities) across multiple data sets.
consensusMEDissimilarity
Consensus dissimilarity of module eigengenes.
conformityBasedNetworkConcepts
Calculation of conformity-based network concepts.
networkConcepts
Calculations of network concepts
stratifiedBarplot
Bar plots of data across two splitting parameters
goodSamplesGenesMS
Iterative filtering of samples and genes with too many missing entries across multiple data sets
addGrid
Add grid lines to an existing plot.
moduleColor.getMEprefix
Get the prefix used to label module eigengenes.
goodGenes
Filter genes with too many missing entries
goodGenesMS
Filter genes with too many missing entries across multiple sets
intramodularConnectivity
Calculation of intramodular connectivity
goodSamplesGenes
Iterative filtering of samples and genes with too many missing entries
fundamentalNetworkConcepts
Calculation of fundamental network concepts from an adjacency matrix.
scaleFreePlot
Visual check of scale-free topology
populationMeansInAdmixture
Estimate the population-specific mean values in an admixed population.
mutualInfoAdjacency
Calculate weighted adjacency matrices based on mutual information
plotDendroAndColors
Dendrogram plot with color annotation of objects
nearestNeighborConnectivity
Connectivity to a constant number of nearest neighbors
plotClusterTreeSamples
Annotated clustering dendrogram of microarray samples
cutreeStaticColor
Constant height tree cut using color labels
moduleNumber
Fixed-height cut of a dendrogram.
simulateDatExpr5Modules
Simplified simulation of expression data
exportNetworkToCytoscape
Export network to Cytoscape
nearestCentroidPredictor
Nearest centroid predictor
plotNetworkHeatmap
Network heatmap plot
coxRegressionResiduals
Deviance- and martingale residuals from a Cox regression model
simulateModule
Simulate a gene co-expression module
consensusDissTOMandTree
Consensus clustering based on topological overlap and hierarchical clustering
multiSetMEs
Calculate module eigengenes.
accuracyMeasures
Accuracy measures for a 2x2 confusion matrix.
colQuantileC
Fast colunm-wise quantile of a matrix.
chooseOneHubInEachModule
Chooses a single hub gene in each module
conformityDecomposition
Conformity and module based decomposition of a network adjacency matrix.
propVarExplained
Proportion of variance explained by eigengenes.
TOMsimilarity
Topological overlap matrix similarity and dissimilarity
pquantile
Parallel quantile, median, mean
addTraitToMEs
Add trait information to multi-set module eigengene structure
pickHardThreshold
Analysis of scale free topology for hard-thresholding.
matchLabels
Relabel module labels to best match the given reference labels
prepComma
Prepend a comma to a non-empty string
alignExpr
Align expression data with given vector
moduleMergeUsingKME
Merge modules and reassign genes using kME.
orderMEs
Put close eigenvectors next to each other
metaAnalysis
Meta-analysis of binary and continuous variables
consensusProjectiveKMeans
Consensus projective K-means (pre-)clustering of expression data
labelPoints
Label scatterplot points
labeledBarplot
Barplot with text or color labels.
collectGarbage
Iterative garbage collection.
corPredictionSuccess
Qunatification of success of gene screening
coClustering.permutationTest
Permutation test for co-clustering
fixDataStructure
Put single-set data into a form useful for multiset calculations.
nearestNeighborConnectivityMS
Connectivity to a constant number of nearest neighbors across multiple data sets
overlapTable
Calculate overlap of modules
hubGeneSignificance
Hubgene significance
redWhiteGreen
Red-white-green color sequence
labels2colors
Convert numerical labels to colors.
mergeCloseModules
Merge close modules in gene expression data
kMEcomparisonScatterplot
Function to plot kME values between two comparable data sets.
automaticNetworkScreeningGS
One-step automatic network gene screening with external gene significance
corPvalueFisher
Fisher's asymptotic p-value for correlation
relativeCorPredictionSuccess
Compare prediction success
TOMsimilarityFromExpr
Topological overlap matrix
GOenrichmentAnalysis
Calculation of GO enrichment (experimental)
sigmoidAdjacencyFunction
Sigmoid-type adacency function.
rankPvalue
Estimate the p-value for ranking consistently high (or low) on multiple lists
GTOMdist
Generalized Topological Overlap Measure
corPvalueStudent
Student asymptotic p-value for correlation
pickSoftThreshold
Analysis of scale free topology for soft-thresholding
adjacency.splineReg
Calculate network adjacency based on natural cubic spline regression
chooseTopHubInEachModule
Chooses the top hub gene in each module
removePrincipalComponents
Remove leading principal components from data
proportionsInAdmixture
Estimate the proportion of pure populations in an admixed population based on marker expression values.
signedKME
Signed eigengene-based connectivity
plotMEpairs
Pairwise scatterplots of eigengenes
TOMplot
Graphical representation of the Topological Overlap Matrix
simulateEigengeneNetwork
Simulate eigengene network from a causal model
stdErr
Standard error of the mean of a given vector.
automaticNetworkScreening
One-step automatic network gene screening
signumAdjacencyFunction
Hard-thresholding adjacency function
greenBlackRed
Green-black-red color sequence
metaZfunction
Meta-analysis Z statistic
sizeGrWindow
Opens a graphics window with specified dimensions
Inline display of progress
Inline display of progress
bicorAndPvalue
Calculation of biweight midcorrelations and associated p-values
simulateMultiExpr
Simulate multi-set expression data
rgcolors.func
Red and Green Color Specification
plotMat
Red and Green Color Image of Data Matrix
stat.diag.da
Diagonal Discriminant Analysis
checkAdjMat
Check adjacency matrix
stat.bwss
Between and Within Group Sum of Squares Calculation
numbers2colors
Color representation for a numeric variable
adjacency
Calculate network adjacency
projectiveKMeans
Projective K-means (pre-)clustering of expression data
standardColors
Colors this library uses for labeling modules.
simulateSmallLayer
Simulate small modules
qvalue
Estimate the q-values for a given set of p-values
randIndex
Rand index of two partitions
removeGreyME
Removes the grey eigengene from a given collection of eigengenes.
blockwiseModules
Automatic network construction and module detection
correlationPreservation
Preservation of eigengene correlations
labeledHeatmap
Produce a labeled heatmap plot
recutBlockwiseTrees
Repeat blockwise module detection from pre-calculated data
recutConsensusTrees
Repeat blockwise consensus module detection from pre-calculated data
collapseRowsUsingKME
Selects one representative row per group based on kME
simulateDatExpr
Simulation of expression data
spaste
Space-less paste
cor
Fast calculations of Pearson correlation.
exportNetworkToVisANT
Export network data in format readable by VisANT
networkScreening
Identification of genes related to a trait
softConnectivity
Calculates connectivity of a weighted network.
plotEigengeneNetworks
Eigengene network plot
standardScreeningNumericTrait
Standard screening for numeric traits
standardScreeningCensoredTime
Standard Screening with regard to a Censored Time Variable
vectorizeMatrix
Turn a matrix into a vector of non-redundant components
verboseScatterplot
Scatterplot annotated by regression line and p-value
unsignedAdjacency
Calculation of unsigned adjacency
verboseBarplot
Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
verboseBoxplot
Boxplot annotated by a Kruskal-Wallis p-value
votingLinearPredictor
Voting linear predictor
setCorrelationPreservation
Summary correlation preservation measure
userListEnrichment
Measure enrichment between inputted and user-defined lists
verboseIplot
Scatterplot with density
subsetTOM
Topological overlap for a subset of a whole set of genes
dynamicMergeCut
Threshold for module merging
greenWhiteRed
Green-white-red color sequence
scaleFreeFitIndex
Calculation of fitting statistics for evaluating scale free topology fit.
vectorTOM
Topological overlap for a subset of the whole set of genes
addErrorBars
Add error bars to a barplot.
collapseRows
Select one representative row per group
keepCommonProbes
Keep probes that are shared among given data sets
na
Basic Statistical Functions for Handling Missing Values
normalizeLabels
Transform numerical labels into normal order.
orderBranchesUsingHubGenes
Optimize dendrogram using branch swaps and reflections.
plotColorUnderTree
Plot color rows under a dendrogram
overlapTableUsingKME
Determines significant overlap between modules in two networks based on kME tables.
standardScreeningBinaryTrait
Standard screening for binatry traits