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WGCNA (version 1.17)

Weighted Correlation Network Analysis

Description

Functions necessary to perform Weighted Correlation Network Analysis

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Version

Install

install.packages('WGCNA')

Monthly Downloads

11,673

Version

1.17

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

December 7th, 2011

Functions in WGCNA (1.17)

BrainLists

Brain-Related Categories with Corresponding Gene Markers

TOMsimilarity

Topological overlap matrix similarity and dissimilarity

cutreeStaticColor

Constant height tree cut using color labels

standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable

coxRegressionResiduals

Deviance- and martingale residuals from a Cox regression model

hubGeneSignificance

Hubgene significance

alignExpr

Align expression data with given vector

redWhiteGreen

Red-white-green color sequence

modulePreservation

Calculation of module preservation statistics

consensusOrderMEs

Put close eigenvectors next to each other in several sets.

mergeCloseModules

Merge close modules in gene expression data

adjacency

Calculate network adjacency

greenWhiteRed

Green-white-red color sequence

nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors

unsignedAdjacency

Calculation of unsigned adjacency

prepComma

Prepend a comma to a non-empty string

propVarExplained

Proportion of variance explained by eigengenes.

scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.

cutreeStatic

Constant-height tree cut

simulateEigengeneNetwork

Simulate eigengene network from a causal model

collapseRows

Select one representative row per group

projectiveKMeans

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

WGCNA-package

Weighted Gene Co-Expression Network Analysis

chooseOneHubInEachModule

Chooses a single hub gene in each module

verboseBoxplot

Boxplot annotated by a Kruskal-Wallis p-value

blockwiseModules

Automatic network construction and module detection

verboseBarplot

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

consensusProjectiveKMeans

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

consensusDissTOMandTree

Consensus clustering based on topological overlap and hierarchical clustering

plotCor

Red and Green Color Image of Correlation Matrix

SCsLists

Stem Cell-Related Genes with Corresponding Gene Markers

vectorTOM

Topological overlap for a subset of the whole set of genes

networkScreening

Identification of genes related to a trait

addGrid

Add grid lines to an existing plot.

coClustering

Co-clustering measure of cluster preservation between two clusterings

qvalue

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

orderMEs

Put close eigenvectors next to each other

addErrorBars

Add error bars to a barplot.

goodGenes

Filter genes with too many missing entries

corPvalueFisher

Fisher's asymptotic p-value for correlation

AFcorMI

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation

GOenrichmentAnalysis

Calculation of GO enrichment (experimental)

goodSamples

Filter samples with too many missing entries

verboseIplot

Scatterplot with density

checkSets

Check structure and retrieve sizes of a group of datasets.

mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information

plotModuleSignificance

Barplot of module significance

setCorrelationPreservation

Summary correlation preservation measure

simulateModule

Simulate a gene co-expression module

consensusKME

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

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

bicor

Biweight Midcorrelation

goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries

kMEcomparisonScatterplot

Function to plot kME values between two comparable data sets.

recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data

labeledBarplot

Barplot with text or color labels.

exportNetworkToVisANT

Export network data in format readable by VisANT

blockwiseConsensusModules

Find consensus modules across several datasets.

greenBlackRed

Green-black-red color sequence

TOMplot

Graphical representation of the Topological Overlap Matrix

allowWGCNAThreads

Allow and disable multi-threading for certain WGCNA calculations

nearestCentroidPredictor

Nearest centroid predictor

removeGreyME

Removes the grey eigengene from a given collection of eigengenes.

metaAnalysis

Meta-analysis of binary and continuous variables

cor

Fast calculations of Pearson correlation.

Inline display of progress

matrixToNetwork

Construct a network from a matrix

plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples

moduleNumber

Fixed-height cut of a dendrogram.

overlapTable

Calculate overlap of modules

collapseRowsUsingKME

Selects one representative row per group based on kME

checkAdjMat

Check adjacency matrix

BloodLists

Blood Cell Types with Corresponding Gene Markers

bicorAndPvalue

Calculation of biweight midcorrelations and associated p-values

intramodularConnectivity

Calculation of intramodular connectivity

correlationPreservation

Preservation of eigengene correlations

corPredictionSuccess

Qunatification of success of gene screening

moduleMergeUsingKME

Merge modules and reassign genes using kME.

scaleFreePlot

Visual check of scale-free topology

consensusMEDissimilarity

Consensus dissimilarity of module eigengenes.

plotColorUnderTree

Plot color rows under a dendrogram

adjacency.splineReg

Calculate network adjacency based on natural cubic spline regression

displayColors

Show colors used to label modules

TOMsimilarityFromExpr

Topological overlap matrix

colQuantileC

Fast colunm-wise quantile of a matrix.

simulateSmallLayer

Simulate small modules

labels2colors

Convert numerical labels to colors.

dynamicMergeCut

Threshold for module merging

coClustering.permutationTest

Permutation test for co-clustering

automaticNetworkScreening

One-step automatic network gene screening

signumAdjacencyFunction

Hard-thresholding adjacency function

networkConcepts

Calculations of network concepts

moduleColor.getMEprefix

Get the prefix used to label module eigengenes.

plotMat

Red and Green Color Image of Data Matrix

exportNetworkToCytoscape

Export network to Cytoscape

stratifiedBarplot

Bar plots of data across two splitting parameters

labeledHeatmap

Produce a labeled heatmap plot

goodGenesMS

Filter genes with too many missing entries across multiple sets

simulateDatExpr

Simulation of expression data

plotDendroAndColors

Dendrogram plot with color annotation of objects

nPresent

Number of present data entries.

networkScreeningGS

Network gene screening with an external gene significance measure

moduleEigengenes

Calculate module eigengenes.

preservationNetworkConnectivity

Network preservation calculations

numbers2colors

Color representation for a numeric variable

standardScreeningBinaryTrait

Standard screening for binatry traits

goodSamplesMS

Filter samples with too many missing entries across multiple data sets

signedKME

Signed eigengene-based connectivity

multiSetMEs

Calculate module eigengenes.

recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data

rankPvalue

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

sizeGrWindow

Opens a graphics window with specified dimensions

fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.

randIndex

Rand index of two partitions

simulateMultiExpr

Simulate multi-set expression data

stat.diag.da

Diagonal Discriminant Analysis

userListEnrichment

Measure enrichment between inputted and user-defined lists

verboseScatterplot

Scatterplot annotated by regression line and p-value

relativeCorPredictionSuccess

Compare prediction success

overlapTableUsingKME

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

goodSamplesGenesMS

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

keepCommonProbes

Keep probes that are shared among given data sets

plotMEpairs

Pairwise scatterplots of eigengenes

softConnectivity

Calculates connectivity of a weighted network.

clusterCoef

Clustering coefficient calculation

matchLabels

Relabel module labels to best match the given reference labels

votingLinearPredictor

Voting linear predictor

sigmoidAdjacencyFunction

Sigmoid-type adacency function.

standardScreeningNumericTrait

Standard screening for numeric traits

proportionsInAdmixture

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

spaste

Space-less paste

metaZfunction

Meta-analysis Z statistic

orderBranchesUsingHubGenes

Optimize dendrogram using branch swaps and reflections.

Basic Statistical Functions for Handling Missing Values

standardColors

Colors this library uses for labeling modules.

addTraitToMEs

Add trait information to multi-set module eigengene structure

adjacency.polyReg

Adjacency matrix based on polynomial regression

addGuideLines

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

corAndPvalue

Calculation of correlations and associated p-values

conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.

corPvalueStudent

Student asymptotic p-value for correlation

populationMeansInAdmixture

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

collectGarbage

Iterative garbage collection.

pickSoftThreshold

Analysis of scale free topology for soft-thresholding

plotEigengeneNetworks

Eigengene network plot

nearestNeighborConnectivityMS

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

subsetTOM

Topological overlap for a subset of a whole set of genes

stdErr

Standard error of the mean of a given vector.

plotNetworkHeatmap

Network heatmap plot

normalizeLabels

Transform numerical labels into normal order.

swapTwoBranches

Select, swap, or reflect branches in a dendrogram.

removePrincipalComponents

Remove leading principal components from data

qvalue.restricted

qvalue convenience wrapper

GTOMdist

Generalized Topological Overlap Measure

accuracyMeasures

Accuracy measures for a 2x2 confusion matrix.

chooseTopHubInEachModule

Chooses the top hub gene in each module

pickHardThreshold

Analysis of scale free topology for hard-thresholding.

rgcolors.func

Red and Green Color Specification

simulateDatExpr5Modules

Simplified simulation of expression data

vectorizeMatrix

Turn a matrix into a vector of non-redundant components

fixDataStructure

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

labelPoints

Label scatterplot points

multiData.eigengeneSignificance

Eigengene significance across multiple sets

conformityDecomposition

Conformity and module based decomposition of a network adjacency matrix.

pquantile

Parallel quantile, median, mean

stat.bwss

Between and Within Group Sum of Squares Calculation