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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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Version

Install

install.packages('WGCNA')

Monthly Downloads

16,020

Version

1.13

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

August 18th, 2011

Functions in WGCNA (1.13)

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

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.

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