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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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Version

Install

install.packages('WGCNA')

Monthly Downloads

16,020

Version

1.11-2

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

June 6th, 2011

Functions in WGCNA (1.11-2)

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