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WGCNA (version 1.48)

Weighted Correlation Network Analysis

Description

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

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Version

Install

install.packages('WGCNA')

Monthly Downloads

16,020

Version

1.48

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

October 29th, 2015

Functions in WGCNA (1.48)

Topological overlap matrix similarity and dissimilarity

Estimate the true trait underlying a list of surrogate markers.

allowWGCNAThreads

Allow and disable multi-threading for certain WGCNA calculations

blockwiseModules

Automatic network construction and module detection

accuracyMeasures

Accuracy measures for a 2x2 confusion matrix or for vectors of predicted and observed values.

Check adjacency matrix

kMEcomparisonScatterplot

Function to plot kME values between two comparable data sets.

Fast colunm- and row-wise quantile of a matrix.

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

Stem Cell-Related Genes with Corresponding Gene Markers

Align expression data with given vector

coxRegressionResiduals

Deviance- and martingale residuals from a Cox regression model

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation

consensusProjectiveKMeans

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

Graphical representation of the Topological Overlap Matrix

Produce a labeled heatmap plot

Add trait information to multi-set module eigengene structure

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

projectiveKMeans

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

adjacency.splineReg

Calculate network adjacency based on natural cubic spline regression

blockwiseIndividualTOMs

Calculation of block-wise topological overlaps

Consensus network (topological overlap).

corPredictionSuccess

Qunatification of success of gene screening

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

Filter genes with too many missing entries across multiple sets

branchSplit.dissim

Branch split based on dissimilarity.

moduleEigengenes

Calculate module eigengenes.

automaticNetworkScreening

One-step automatic network gene screening

Calculation of biweight midcorrelations and associated p-values

goodSamplesGenesMS

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

adjacency.polyReg

Adjacency matrix based on polynomial regression

Number of present data entries.

populationMeansInAdmixture

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

Check structure and retrieve sizes of a group of datasets.

chooseOneHubInEachModule

Chooses a single hub gene in each module

Weights used in biweight midcovariance

Blue-white-red color sequence

Iterative garbage collection.

fixDataStructure

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

mtd.setColnames

Get and set column names in a multiData structure.

Inline display of progress

Inline display of progress

Blood Cell Types with Corresponding Gene Markers

Relabel module labels to best match the given reference labels

Put close eigenvectors next to each other

Determine whether the supplied object is a valid multiData structure

Union and intersection of multiple sets

dynamicMergeCut

Threshold for module merging

conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.

standardScreeningBinaryTrait

Standard screening for binatry traits

normalizeLabels

Transform numerical labels into normal order.

stratifiedBarplot

Bar plots of data across two splitting parameters

networkScreeningGS

Network gene screening with an external gene significance measure

Fixed-height cut of a dendrogram.

chooseTopHubInEachModule

Chooses the top hub gene in each module

Generalized Topological Overlap Measure

overlapTableUsingKME

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

correlationPreservation

Preservation of eigengene correlations

Green-black-red color sequence

exportNetworkToCytoscape

Export network to Cytoscape

setCorrelationPreservation

Summary correlation preservation measure

proportionsInAdmixture

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

swapTwoBranches

Select, swap, or reflect branches in a dendrogram.

preservationNetworkConnectivity

Network preservation calculations

branchEigengeneDissim

Branch dissimilarity based on eigennodes (eigengenes).

hubGeneSignificance

Hubgene significance

Red-white-green color sequence

Pathways with Corresponding Gene Markers - Compiled by Mike Palazzolo and Jim Wang from CHDI

Filter genes with too many missing entries

Clustering coefficient calculation

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

Barplot with text or color labels.

Convert a list to a multiData structure and vice-versa.

Constant-height tree cut

BrainRegionMarkers

Gene Markers for Regions of the Human Brain

consensusDissTOMandTree

Consensus clustering based on topological overlap and hierarchical clustering

Biweight Midcorrelation

ImmunePathwayLists

Immune Pathways with Corresponding Gene Markers

nearestNeighborConnectivityMS

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

Co-clustering measure of cluster preservation between two clusterings

networkConcepts

Calculations of network concepts

exportNetworkToVisANT

Export network data in format readable by VisANT

fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.

Topological overlap for a subset of the whole set of genes

orderBranchesUsingHubGenes

Optimize dendrogram using branch swaps and reflections.

pickSoftThreshold

Analysis of scale free topology for soft-thresholding

collapseRowsUsingKME

Selects one representative row per group based on kME

Add error bars to a barplot.

labeledHeatmap.multiPage

Labeled heatmap divided into several separate plots.

signumAdjacencyFunction

Hard-thresholding adjacency function

userListEnrichment

Measure enrichment between inputted and user-defined lists

consensusOrderMEs

Put close eigenvectors next to each other in several sets.

Filter samples with too many missing entries

Add grid lines to an existing plot.

coClustering.permutationTest

Permutation test for co-clustering

conformityDecomposition

Conformity and module based decomposition of a network adjacency matrix.

Calculate module eigengenes.

branchSplitFromStabilityLabels

Branch split (dissimilarity) statistic derived from labels determined from a stability study

Create a multiData structure.

simulateSmallLayer

Simulate small modules

networkScreening

Identification of genes related to a trait

Red and Green Color Image of Correlation Matrix

sigmoidAdjacencyFunction

Sigmoid-type adacency function.

lowerTri2matrix

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

Select one representative row per group

corPvalueStudent

Student asymptotic p-value for correlation

If possible, simplify a multiData structure to a 3-dimensional array.

TOMsimilarityFromExpr

Topological overlap matrix

Number of sets in a multi-set variable

vectorizeMatrix

Turn a matrix into a vector of non-redundant components

Calculation of correlations and associated p-values

Convert numerical labels to colors.

Colors this library uses for labeling modules.

nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors

transposeBigData

Transpose a big matrix or data frame

Break long character strings into multiple lines

mergeCloseModules

Merge close modules in gene expression data

consensusMEDissimilarity

Consensus dissimilarity of module eigengenes.

intramodularConnectivity

Calculation of intramodular connectivity

keepCommonProbes

Keep probes that are shared among given data sets

Green-white-red color sequence

corPvalueFisher

Fisher's asymptotic p-value for correlation

Pairwise scatterplots of eigengenes

moduleColor.getMEprefix

Get the prefix used to label module eigengenes.

recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data

Fast calculations of Pearson correlation.

Pad numbers with leading zeros to specified total width

scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.

simulateEigengeneNetwork

Simulate eigengene network from a causal model

plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples

Boxplot annotated by a Kruskal-Wallis p-value

moduleMergeUsingKME

Merge modules and reassign genes using kME.

Signed eigengene-based connectivity

unsignedAdjacency

Calculation of unsigned adjacency

Label scatterplot points

qvalue.restricted

qvalue convenience wrapper

simulateMultiExpr

Simulate multi-set expression data

Red and Green Color Specification

Show colors used to label modules

Standard error of the mean of a given vector.

Apply a function to each set in a multiData structure.

Prepend a comma to a non-empty string

mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information

plotDendroAndColors

Dendrogram plot with color annotation of objects

Topological overlap for a subset of a whole set of genes

modulePreservation

Calculation of module preservation statistics

simulateDatExpr5Modules

Simplified simulation of expression data

simulateDatExpr

Simulation of expression data

recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data

Red and Green Color Image of Data Matrix

Calculate network adjacency

Opens a graphics window with specified dimensions

multiData.eigengeneSignificance

Eigengene significance across multiple sets

matrixToNetwork

Construct a network from a matrix

Color representation for a numeric variable

Space-less paste

removePrincipalComponents

Remove leading principal components from data

nearestCentroidPredictor

Nearest centroid predictor

plotColorUnderTree

Plot color rows in a given order, for example under a dendrogram

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

plotModuleSignificance

Barplot of module significance

Parallel quantile, median, mean

Turn a multiData structure into a single matrix or data frame.

cutreeStaticColor

Constant height tree cut using color labels

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

Subset rows and columns in a multiData structure

votingLinearPredictor

Voting linear predictor

Simulate a gene co-expression module

Filter samples with too many missing entries across multiple data sets

verboseScatterplot

Scatterplot annotated by regression line and p-value

Divide tasks among workers

softConnectivity

Calculates connectivity of a weighted network.

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

Rand index of two partitions

pickHardThreshold

Analysis of scale free topology for hard-thresholding.

propVarExplained

Proportion of variance explained by eigengenes.

GOenrichmentAnalysis

Calculation of GO enrichment (experimental)

plotEigengeneNetworks

Eigengene network plot

Visual check of scale-free topology

plotNetworkHeatmap

Network heatmap plot

relativeCorPredictionSuccess

Compare prediction success

Brain-Related Categories with Corresponding Gene Markers

empiricalBayesLM

Empirical Bayes-moderated adjustment for unwanted covariates

returnGeneSetsAsList

Return pre-defined gene lists in several biomedical categories.

Weighted Gene Co-Expression Network Analysis

Removes the grey eigengene from a given collection of eigengenes.

standardScreeningNumericTrait

Standard screening for numeric traits

Apply a function to elements of given multiData structures.

Meta-analysis Z statistic

goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries

blockwiseConsensusModules

Find consensus modules across several datasets.

standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable

Scatterplot with density

Meta-analysis of binary and continuous variables

Set attributes on each component of a multiData structure

Calculate overlap of modules

Shorten given character strings by truncating at a suitable separator.