Learn R Programming
⚠️There's a newer version (1.73) of this package.Take me there.

WGCNA (version 1.25-1)

Weighted Correlation Network Analysis

Description

Functions necessary to perform Weighted Correlation Network Analysis

Copy Link

Version

Install

install.packages('WGCNA')

Monthly Downloads

16,961

Version

1.25-1

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

November 9th, 2012

Functions in WGCNA (1.25-1)

collectGarbage

Iterative garbage collection.
adjacency

Calculate network adjacency
TOMplot

Graphical representation of the Topological Overlap Matrix
Inline display of progress

Inline display of progress
addGuideLines

Add vertical ``guide lines'' to a dendrogram plot
BrainLists

Brain-Related Categories with Corresponding Gene Markers
GOenrichmentAnalysis

Calculation of GO enrichment (experimental)
consensusDissTOMandTree

Consensus clustering based on topological overlap and hierarchical clustering
BrainRegionMarkers

Gene Markers for Regions of the Human Brain
AFcorMI

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
consensusOrderMEs

Put close eigenvectors next to each other in several sets.
dynamicMergeCut

Threshold for module merging
overlapTable

Calculate overlap of modules
spaste

Space-less paste
greenBlackRed

Green-black-red color sequence
blockSize

Attempt to calculate an appropriate block size to maximize efficiency of block-wise calcualtions.
simulateEigengeneNetwork

Simulate eigengene network from a causal model
GTOMdist

Generalized Topological Overlap Measure
greenWhiteRed

Green-white-red color sequence
chooseTopHubInEachModule

Chooses the top hub gene in each module
simulateModule

Simulate a gene co-expression module
projectiveKMeans

Projective K-means (pre-)clustering of expression data
orderMEs

Put close eigenvectors next to each other
plotModuleSignificance

Barplot of module significance
lowerTri2matrix

Reconstruct a symmetric matrix from a distance (lower-triangular) representation
labelPoints

Label scatterplot points
signumAdjacencyFunction

Hard-thresholding adjacency function
keepCommonProbes

Keep probes that are shared among given data sets
goodGenesMS

Filter genes with too many missing entries across multiple sets
matchLabels

Relabel module labels to best match the given reference labels
na

Basic Statistical Functions for Handling Missing Values
multiSetMEs

Calculate module eigengenes.
networkScreening

Identification of genes related to a trait
votingLinearPredictor

Voting linear predictor
checkAdjMat

Check adjacency matrix
stratifiedBarplot

Bar plots of data across two splitting parameters
plotMat

Red and Green Color Image of Data Matrix
bicor

Biweight Midcorrelation
standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable
SCsLists

Stem Cell-Related Genes with Corresponding Gene Markers
TOMsimilarity

Topological overlap matrix similarity and dissimilarity
standardScreeningNumericTrait

Standard screening for numeric traits
randomGLMpredictor

Random generalized linear model predictor
simulateSmallLayer

Simulate small modules
networkScreeningGS

Network gene screening with an external gene significance measure
rgcolors.func

Red and Green Color Specification
allocateJobs

Divide tasks among workers
stat.diag.da

Diagonal Discriminant Analysis
exportNetworkToVisANT

Export network data in format readable by VisANT
goodSamplesGenesMS

Iterative filtering of samples and genes with too many missing entries across multiple data sets
metaZfunction

Meta-analysis Z statistic
populationMeansInAdmixture

Estimate the population-specific mean values in an admixed population.
userListEnrichment

Measure enrichment between inputted and user-defined lists
simulateMultiExpr

Simulate multi-set expression data
simulateDatExpr5Modules

Simplified simulation of expression data
randIndex

Rand index of two partitions
standardScreeningBinaryTrait

Standard screening for binatry traits
vectorTOM

Topological overlap for a subset of the whole set of genes
checkSets

Check structure and retrieve sizes of a group of datasets.
blockwiseModules

Automatic network construction and module detection
verboseBarplot

Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
simulateDatExpr

Simulation of expression data
addGrid

Add grid lines to an existing plot.
plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples
addTraitToMEs

Add trait information to multi-set module eigengene structure
recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data
blockwiseConsensusModules

Find consensus modules across several datasets.
TrueTrait

Estimate the true trait underlying a list of surrogate markers.
scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.
addErrorBars

Add error bars to a barplot.
blueWhiteRed

Blue-white-red color sequence
clusterCoef

Clustering coefficient calculation
cor

Fast calculations of Pearson correlation.
mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information
chooseOneHubInEachModule

Chooses a single hub gene in each module
colQuantileC

Fast colunm-wise quantile of a matrix.
goodSamples

Filter samples with too many missing entries
coClustering.permutationTest

Permutation test for co-clustering
automaticNetworkScreening

One-step automatic network gene screening
labels2colors

Convert numerical labels to colors.
coxRegressionResiduals

Deviance- and martingale residuals from a Cox regression model
corAndPvalue

Calculation of correlations and associated p-values
displayColors

Show colors used to label modules
numbers2colors

Color representation for a numeric variable
matrixToNetwork

Construct a network from a matrix
allowWGCNAThreads

Allow and disable multi-threading for certain WGCNA calculations
nSets

Number of sets in a multi-set variable
moduleColor.getMEprefix

Get the prefix used to label module eigengenes.
adjacency.splineReg

Calculate network adjacency based on natural cubic spline regression
signedKME

Signed eigengene-based connectivity
corPredictionSuccess

Qunatification of success of gene screening
conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.
swapTwoBranches

Select, swap, or reflect branches in a dendrogram.
moduleNumber

Fixed-height cut of a dendrogram.
multiData.eigengeneSignificance

Eigengene significance across multiple sets
plotColorUnderTree

Plot color rows under a dendrogram
modulePreservation

Calculation of module preservation statistics
plotEigengeneNetworks

Eigengene network plot
recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data
qvalue

Estimate the q-values for a given set of p-values
nearestCentroidPredictor

Nearest centroid predictor
pickHardThreshold

Analysis of scale free topology for hard-thresholding.
labeledBarplot

Barplot with text or color labels.
qvalue.restricted

qvalue convenience wrapper
unsignedAdjacency

Calculation of unsigned adjacency
orderBranchesUsingHubGenes

Optimize dendrogram using branch swaps and reflections.
prepComma

Prepend a comma to a non-empty string
plotNetworkHeatmap

Network heatmap plot
verboseScatterplot

Scatterplot annotated by regression line and p-value
stdErr

Standard error of the mean of a given vector.
plotCor

Red and Green Color Image of Correlation Matrix
labeledHeatmap

Produce a labeled heatmap plot
metaAnalysis

Meta-analysis of binary and continuous variables
relativeCorPredictionSuccess

Compare prediction success
conformityDecomposition

Conformity and module based decomposition of a network adjacency matrix.
adjacency.polyReg

Adjacency matrix based on polynomial regression
blockwiseIndividualTOMs

Calculation of block-wise topological overlaps
collapseRows

Select one representative row per group
consensusKME

Calculate consensus kME (eigengene-based connectivities) across multiple data sets.
corPvalueStudent

Student asymptotic p-value for correlation
automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance
consensusMEDissimilarity

Consensus dissimilarity of module eigengenes.
correlationPreservation

Preservation of eigengene correlations
normalizeLabels

Transform numerical labels into normal order.
intramodularConnectivity

Calculation of intramodular connectivity
kMEcomparisonScatterplot

Function to plot kME values between two comparable data sets.
consensusProjectiveKMeans

Consensus projective K-means (pre-)clustering of expression data
plotDendroAndColors

Dendrogram plot with color annotation of objects
nearestNeighborConnectivityMS

Connectivity to a constant number of nearest neighbors across multiple data sets
preservationNetworkConnectivity

Network preservation calculations
fixDataStructure

Put single-set data into a form useful for multiset calculations.
hubGeneSignificance

Hubgene significance
goodGenes

Filter genes with too many missing entries
collapseRowsUsingKME

Selects one representative row per group based on kME
moduleMergeUsingKME

Merge modules and reassign genes using kME.
corPvalueFisher

Fisher's asymptotic p-value for correlation
moduleEigengenes

Calculate module eigengenes.
verboseIplot

Scatterplot with density
rankPvalue

Estimate the p-value for ranking consistently high (or low) on multiple lists
networkConcepts

Calculations of network concepts
proportionsInAdmixture

Estimate the proportion of pure populations in an admixed population based on marker expression values.
standardColors

Colors this library uses for labeling modules.
pickSoftThreshold

Analysis of scale free topology for soft-thresholding
removePrincipalComponents

Remove leading principal components from data
transposeBigData

Transpose a big matrix or data frame
subsetTOM

Topological overlap for a subset of a whole set of genes
scaleFreePlot

Visual check of scale-free topology
verboseBoxplot

Boxplot annotated by a Kruskal-Wallis p-value
TOMsimilarityFromExpr

Topological overlap matrix
bicorAndPvalue

Calculation of biweight midcorrelations and associated p-values
fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.
goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries
nPresent

Number of present data entries.
vectorizeMatrix

Turn a matrix into a vector of non-redundant components
plotMEpairs

Pairwise scatterplots of eigengenes
propVarExplained

Proportion of variance explained by eigengenes.
sizeGrWindow

Opens a graphics window with specified dimensions
sigmoidAdjacencyFunction

Sigmoid-type adacency function.
BloodLists

Blood Cell Types with Corresponding Gene Markers
ImmunePathwayLists

Immune Pathways with Corresponding Gene Markers
WGCNA-package

Weighted Gene Co-Expression Network Analysis
accuracyMeasures

Accuracy measures for a 2x2 confusion matrix.
alignExpr

Align expression data with given vector
cutreeStatic

Constant-height tree cut
goodSamplesMS

Filter samples with too many missing entries across multiple data sets
mergeCloseModules

Merge close modules in gene expression data
redWhiteGreen

Red-white-green color sequence
removeGreyME

Removes the grey eigengene from a given collection of eigengenes.
setCorrelationPreservation

Summary correlation preservation measure
stat.bwss

Between and Within Group Sum of Squares Calculation
coClustering

Co-clustering measure of cluster preservation between two clusterings
cutreeStaticColor

Constant height tree cut using color labels
exportNetworkToCytoscape

Export network to Cytoscape
nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors
pquantile

Parallel quantile, median, mean
softConnectivity

Calculates connectivity of a weighted network.
overlapTableUsingKME

Determines significant overlap between modules in two networks based on kME tables.