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WGCNA (version 1.43)

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

16,961

Version

1.43

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

January 15th, 2015

Functions in WGCNA (1.43)

Topological overlap matrix similarity and dissimilarity

conformityDecomposition

Conformity and module based decomposition of a network adjacency matrix.

Weighted Gene Co-Expression Network Analysis

moduleMergeUsingKME

Merge modules and reassign genes using kME.

Number of sets in a multi-set variable

Calculate overlap of modules

Graphical representation of the Topological Overlap Matrix

Opens a graphics window with specified dimensions

automaticNetworkScreening

One-step automatic network gene screening

blockwiseConsensusModules

Find consensus modules across several datasets.

GOenrichmentAnalysis

Calculation of GO enrichment (experimental)

Blood Cell Types with Corresponding Gene Markers

Barplot with text or color labels.

Select one representative row per group

consensusMEDissimilarity

Consensus dissimilarity of module eigengenes.

Produce a labeled heatmap plot

Meta-analysis Z statistic

Number of present data entries.

fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.

Color representation for a numeric variable

plotDendroAndColors

Dendrogram plot with color annotation of objects

removePrincipalComponents

Remove leading principal components from data

Filter samples with too many missing entries across multiple data sets

simulateEigengeneNetwork

Simulate eigengene network from a causal model

Green-black-red color sequence

Calculation of correlations and associated p-values

Prepend a comma to a non-empty string

Shorten given character strings by truncating at a suitable separator.

Rand index of two partitions

simulateSmallLayer

Simulate small modules

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

sigmoidAdjacencyFunction

Sigmoid-type adacency function.

setCorrelationPreservation

Summary correlation preservation measure

Filter genes with too many missing entries

fixDataStructure

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

userListEnrichment

Measure enrichment between inputted and user-defined lists

Filter genes with too many missing entries across multiple sets

Align expression data with given vector

Stem Cell-Related Genes with Corresponding Gene Markers

corPredictionSuccess

Qunatification of success of gene screening

mtd.setColnames

Get and set column names in a multiData structure.

mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information

Calculate network adjacency

Iterative garbage collection.

Add trait information to multi-set module eigengene structure

relativeCorPredictionSuccess

Compare prediction success

branchEigengeneDissim

Branch dissimilarity based on eigennodes (eigengenes).

hubGeneSignificance

Hubgene significance

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

coClustering.permutationTest

Permutation test for co-clustering

dynamicMergeCut

Threshold for module merging

goodSamplesGenesMS

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

chooseOneHubInEachModule

Chooses a single hub gene in each module

Clustering coefficient calculation

moduleColor.getMEprefix

Get the prefix used to label module eigengenes.

plotModuleSignificance

Barplot of module significance

proportionsInAdmixture

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

Convert numerical labels to colors.

kMEcomparisonScatterplot

Function to plot kME values between two comparable data sets.

Removes the grey eigengene from a given collection of eigengenes.

Fixed-height cut of a dendrogram.

Fast calculations of Pearson correlation.

cutreeStaticColor

Constant height tree cut using color labels

lowerTri2matrix

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

unsignedAdjacency

Calculation of unsigned adjacency

BrainRegionMarkers

Gene Markers for Regions of the Human Brain

Simulate a gene co-expression module

Brain-Related Categories with Corresponding Gene Markers

Green-white-red color sequence

consensusDissTOMandTree

Consensus clustering based on topological overlap and hierarchical clustering

collapseRowsUsingKME

Selects one representative row per group based on kME

matrixToNetwork

Construct a network from a matrix

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

adjacency.splineReg

Calculate network adjacency based on natural cubic spline regression

Apply a function to elements of given multiData structures.

nearestNeighborConnectivityMS

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

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

exportNetworkToCytoscape

Export network to Cytoscape

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

Calculation of biweight midcorrelations and associated p-values

consensusProjectiveKMeans

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

Meta-analysis of binary and continuous variables

networkScreeningGS

Network gene screening with an external gene significance measure

TOMsimilarityFromExpr

Topological overlap matrix

Subset rows and columns in a multiData structure

plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples

networkScreening

Identification of genes related to a trait

mergeCloseModules

Merge close modules in gene expression data

signumAdjacencyFunction

Hard-thresholding adjacency function

branchSplitFromStabilityLabels

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

standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable

overlapTableUsingKME

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

plotColorUnderTree

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

propVarExplained

Proportion of variance explained by eigengenes.

Divide tasks among workers

orderBranchesUsingHubGenes

Optimize dendrogram using branch swaps and reflections.

chooseTopHubInEachModule

Chooses the top hub gene in each module

projectiveKMeans

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

Union and intersection of multiple sets

Put close eigenvectors next to each other

plotNetworkHeatmap

Network heatmap plot

Red-white-green color sequence

Determine whether the supplied object is a valid multiData structure

Between and Within Group Sum of Squares Calculation

Biweight Midcorrelation

networkConcepts

Calculations of network concepts

Scatterplot with density

Blue-white-red color sequence

branchSplit.dissim

Branch split based on dissimilarity.

swapTwoBranches

Select, swap, or reflect branches in a dendrogram.

Parallel quantile, median, mean

Diagonal Discriminant Analysis

Signed eigengene-based connectivity

moduleEigengenes

Calculate module eigengenes.

vectorizeMatrix

Turn a matrix into a vector of non-redundant components

accuracyMeasures

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

standardScreeningNumericTrait

Standard screening for numeric traits

corPvalueStudent

Student asymptotic p-value for correlation

Create a multiData structure.

votingLinearPredictor

Voting linear predictor

ImmunePathwayLists

Immune Pathways with Corresponding Gene Markers

adjacency.polyReg

Adjacency matrix based on polynomial regression

Label scatterplot points

Space-less paste

Colors this library uses for labeling modules.

Pairwise scatterplots of eigengenes

intramodularConnectivity

Calculation of intramodular connectivity

conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.

labeledHeatmap.multiPage

Labeled heatmap divided into several separate plots.

Consensus network (topological overlap).

simulateMultiExpr

Simulate multi-set expression data

Calculate module eigengenes.

plotEigengeneNetworks

Eigengene network plot

Add grid lines to an existing plot.

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

Topological overlap for a subset of a whole set of genes

Constant-height tree cut

Check adjacency matrix

blockwiseIndividualTOMs

Calculation of block-wise topological overlaps

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation

coxRegressionResiduals

Deviance- and martingale residuals from a Cox regression model

corPvalueFisher

Fisher's asymptotic p-value for correlation

allowWGCNAThreads

Allow and disable multi-threading for certain WGCNA calculations

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

Show colors used to label modules

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

Topological overlap for a subset of the whole set of genes

blockwiseModules

Automatic network construction and module detection

Visual check of scale-free topology

nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors

recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data

Check structure and retrieve sizes of a group of datasets.

recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data

consensusOrderMEs

Put close eigenvectors next to each other in several sets.

Relabel module labels to best match the given reference labels

Co-clustering measure of cluster preservation between two clusterings

simulateDatExpr

Simulation of expression data

Red and Green Color Specification

pickHardThreshold

Analysis of scale free topology for hard-thresholding.

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

returnGeneSetsAsList

Return pre-defined gene lists in several biomedical categories.

correlationPreservation

Preservation of eigengene correlations

transposeBigData

Transpose a big matrix or data frame

normalizeLabels

Transform numerical labels into normal order.

Basic Statistical Functions for Handling Missing Values

goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries

Red and Green Color Image of Correlation Matrix

populationMeansInAdmixture

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

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

stratifiedBarplot

Bar plots of data across two splitting parameters

Break long character strings into multiple lines

modulePreservation

Calculation of module preservation statistics

multiData.eigengeneSignificance

Eigengene significance across multiple sets

Red and Green Color Image of Data Matrix

Boxplot annotated by a Kruskal-Wallis p-value

verboseScatterplot

Scatterplot annotated by regression line and p-value

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

Estimate the true trait underlying a list of surrogate markers.

exportNetworkToVisANT

Export network data in format readable by VisANT

Inline display of progress

Inline display of progress

Apply a function to each set in a multiData structure.

pickSoftThreshold

Analysis of scale free topology for soft-thresholding

nearestCentroidPredictor

Nearest centroid predictor

Pad numbers with leading zeros to specified total width

qvalue.restricted

qvalue convenience wrapper

softConnectivity

Calculates connectivity of a weighted network.

simulateDatExpr5Modules

Simplified simulation of expression data

Generalized Topological Overlap Measure

Add error bars to a barplot.

Filter samples with too many missing entries

keepCommonProbes

Keep probes that are shared among given data sets

Set attributes on each component of a multiData structure

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

scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.

preservationNetworkConnectivity

Network preservation calculations

standardScreeningBinaryTrait

Standard screening for binatry traits

Standard error of the mean of a given vector.