Learn R Programming

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

WGCNA (version 1.70-3)

Weighted Correlation Network Analysis

Description

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) and Langfelder and Horvath (2008) . 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.

Copy Link

Version

Install

install.packages('WGCNA')

Monthly Downloads

16,961

Version

1.70-3

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

February 28th, 2021

Functions in WGCNA (1.70-3)

Blood Cell Types with Corresponding Gene Markers

accuracyMeasures

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

Calculate network adjacency

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation

Add trait information to multi-set module eigengene structure

Various basic operations on BlockwiseData objects.

allowWGCNAThreads

Allow and disable multi-threading for certain WGCNA calculations

Add error bars to a barplot.

Graphical representation of the Topological Overlap Matrix

ImmunePathwayLists

Immune Pathways with Corresponding Gene Markers

Generalized Topological Overlap Measure

branchSplitFromStabilityLabels

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

branchSplit.dissim

Branch split based on dissimilarity.

automaticNetworkScreening

One-step automatic network gene screening

binarizeCategoricalColumns

Turn categorical columns into sets of binary indicators

Add grid lines to an existing plot.

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

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

BrainRegionMarkers

Gene Markers for Regions of the Human Brain

adjacency.polyReg

Adjacency matrix based on polynomial regression

GOenrichmentAnalysis

Calculation of GO enrichment (experimental)

Stem Cell-Related Genes with Corresponding Gene Markers

Topological overlap matrix similarity and dissimilarity

Calculation of biweight midcorrelations and associated p-values

binarizeCategoricalVariable

Turn a categorical variable into a set of binary indicators

Estimate the true trait underlying a list of surrogate markers.

collapseRowsUsingKME

Selects one representative row per group based on kME

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

Biweight Midcorrelation

TOMsimilarityFromExpr

Topological overlap matrix

Check structure and retrieve sizes of a group of datasets.

blockwiseConsensusModules

Find consensus modules across several datasets.

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

adjacency.splineReg

Calculate network adjacency based on natural cubic spline regression

Check adjacency matrix

chooseOneHubInEachModule

Chooses a single hub gene in each module

Align expression data with given vector

consensusTreeInputs

Get all elementary inputs in a consensus tree

convertNumericColumnsToNumeric

Convert character columns that represent numbers to numeric

conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.

Divide tasks among workers

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

Blue-white-red color sequence

Weights used in biweight midcovariance

Iterative garbage collection.

consensusOrderMEs

Put close eigenvectors next to each other in several sets.

conformityDecomposition

Conformity and module based decomposition of a network adjacency matrix.

Filter samples with too many missing entries

blockwiseModules

Automatic network construction and module detection

Co-clustering measure of cluster preservation between two clusterings

blockwiseIndividualTOMs

Calculation of block-wise topological overlaps

consensusProjectiveKMeans

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

kMEcomparisonScatterplot

Function to plot kME values between two comparable data sets.

matrixToNetwork

Construct a network from a matrix

mergeCloseModules

Merge close modules in gene expression data

goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries

keepCommonProbes

Keep probes that are shared among given data sets

branchEigengeneDissim

Branch dissimilarity based on eigennodes (eigengenes).

coClustering.permutationTest

Permutation test for co-clustering

chooseTopHubInEachModule

Chooses the top hub gene in each module

Clustering coefficient calculation

consensusRepresentatives

Consensus selection of group representatives

dynamicMergeCut

Threshold for module merging

hierarchicalConsensusMEDissimilarity

Hierarchical consensus calculation of module eigengene dissimilarity

hierarchicalConsensusModules

Hierarchical consensus network construction and module identification

empiricalBayesLM

Empirical Bayes-moderated adjustment for unwanted covariates

Consensus network (topological overlap).

Fast calculations of Pearson correlation.

consensusDissTOMandTree

Consensus clustering based on topological overlap and hierarchical clustering

consensusCalculation

Calculation of a (single) consenus with optional data calibration.

Fixed-height cut of a dendrogram.

Calculation of correlations and associated p-values

Produce a labeled heatmap plot

Show colors used to label modules

cutreeStaticColor

Constant height tree cut using color labels

modulePreservation

Calculation of module preservation statistics

Green-white-red color sequence

hierarchicalConsensusCalculation

Hierarchical consensus calculation

Green-black-red color sequence

hierarchicalConsensusKME

Calculation of measures of fuzzy module membership (KME) in hierarchical consensus modules

Number of sets in a multi-set variable

moduleEigengenes

Calculate module eigengenes.

moduleMergeUsingKME

Merge modules and reassign genes using kME.

exportNetworkToCytoscape

Export network to Cytoscape

lowerTri2matrix

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

corPvalueStudent

Student asymptotic p-value for correlation

labeledHeatmap.multiPage

Labeled heatmap divided into several separate plots.

factorizeNonNumericColumns

Turn non-numeric columns into factors

correlationPreservation

Preservation of eigengene correlations

fixDataStructure

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

newBlockwiseData

Create, merge and expand BlockwiseData objects

newConsensusOptions

Create a list holding consensus calculation options.

nearestCentroidPredictor

Nearest centroid predictor

Filter genes with too many missing entries

mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information

Color representation for a numeric variable

Number of present data entries.

Red and Green Color Image of Data Matrix

exportNetworkToVisANT

Export network data in format readable by VisANT

plotModuleSignificance

Barplot of module significance

Select one representative row per group

Relabel module labels to best match the given reference labels

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

Subset rows and columns in a multiData structure

Break long character strings into multiple lines

multiData.eigengeneSignificance

Eigengene significance across multiple sets

Analogs of grep(l) and (g)sub for multiple patterns and relacements

consensusMEDissimilarity

Consensus dissimilarity of module eigengenes.

Create a multiData structure.

newConsensusTree

Create a new consensus tree

Calculate individual correlation network matrices

fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.

Filter genes with too many missing entries across multiple sets

newCorrelationOptions

Creates a list of correlation options.

corPredictionSuccess

Qunatification of success of gene screening

Inline display of progress

Inline display of progress

Prepend a comma to a non-empty string

Pad numbers with leading zeros to specified total width

Red-white-green color sequence

corPvalueFisher

Fisher's asymptotic p-value for correlation

pickSoftThreshold

Analysis of scale free topology for soft-thresholding

pickHardThreshold

Analysis of scale free topology for hard-thresholding.

pruneAndMergeConsensusModules

Iterative pruning and merging of (hierarchical) consensus modules

Red and Green Color Specification

relativeCorPredictionSuccess

Compare prediction success

orderBranchesUsingHubGenes

Optimize dendrogram using branch swaps and reflections.

softConnectivity

Calculates connectivity of a weighted network.

sampledBlockwiseModules

Blockwise module identification in sampled data

Space-less paste

Topological overlap for a subset of a whole set of genes

coxRegressionResiduals

Deviance- and martingale residuals from a Cox regression model

Parallel quantile, median, mean

Label scatterplot points

populationMeansInAdmixture

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

Replace missing values with a constant.

simulateMultiExpr

Simulate multi-set expression data

selectFewestConsensusMissing

Select columns with the lowest consensus number of missing data

pruneConsensusModules

Prune (hierarchical) consensus modules by removing genes with low eigengene-based intramodular connectivity

returnGeneSetsAsList

Return pre-defined gene lists in several biomedical categories.

hubGeneSignificance

Hubgene significance

Visual check of scale-free topology

simulateSmallLayer

Simulate small modules

Rand index of two partitions

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

goodSamplesGenesMS

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

hierarchicalConsensusTOM

Calculation of hierarchical consensus topological overlap matrix

Filter samples with too many missing entries across multiple data sets

transposeBigData

Transpose a big matrix or data frame

Constant-height tree cut

unsignedAdjacency

Calculation of unsigned adjacency

hierarchicalMergeCloseModules

Merge close (similar) hierarchical consensus modules

verboseScatterplot

Scatterplot annotated by regression line and p-value

votingLinearPredictor

Voting linear predictor

Barplot with text or color labels.

Impute missing data separately in each module

Determine whether the supplied object is a valid multiData structure

Meta-analysis Z statistic

setCorrelationPreservation

Summary correlation preservation measure

Meta-analysis of binary and continuous variables

intramodularConnectivity

Calculation of intramodular connectivity

Opens a graphics window with specified dimensions

simulateEigengeneNetwork

Simulate eigengene network from a causal model

Fast joint calculation of row- or column-wise minima and indices of minimum elements

Shorten given character strings by truncating at a suitable separator.

Simulate a gene co-expression module

Convert numerical labels to colors.

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

mtd.setColnames

Get and set column names in a multiData structure.

vectorizeMatrix

Turn a matrix into a vector of non-redundant components

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

sizeRestrictedClusterMerge

Cluter merging with size restrictions

swapTwoBranches

Select, swap, or reflect branches in a dendrogram.

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

moduleColor.getMEprefix

Get the prefix used to label module eigengenes.

networkScreeningGS

Network gene screening with an external gene significance measure

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

nearestNeighborConnectivityMS

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

nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors

Apply a function to each set in a multiData structure.

Calculate overlap of modules

Apply a function to elements of given multiData structures.

newBlockInformation

Create a list holding information about dividing data into blocks

overlapTableUsingKME

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

plotNetworkHeatmap

Network heatmap plot

Plot multiple histograms in a single plot

Calculate module eigengenes.

Union and intersection of multiple sets

networkScreening

Identification of genes related to a trait

networkConcepts

Calculations of network concepts

normalizeLabels

Transform numerical labels into normal order.

Set attributes on each component of a multiData structure

newNetworkOptions

Create a list of network construction arguments (options).

Put close eigenvectors next to each other

plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples

propVarExplained

Proportion of variance explained by eigengenes.

Standard error of the mean of a given vector.

simulateDatExpr5Modules

Simplified simulation of expression data

simulateDatExpr

Simulation of expression data

proportionsInAdmixture

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

orderMEsByHierarchicalConsensus

Order module eigengenes by their hierarchical consensus similarity

Pairwise scatterplots of eigengenes

preservationNetworkConnectivity

Network preservation calculations

Removes the grey eigengene from a given collection of eigengenes.

projectiveKMeans

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

plotEigengeneNetworks

Eigengene network plot

stratifiedBarplot

Bar plots of data across two splitting parameters

removePrincipalComponents

Remove leading principal components from data

scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.

sampledHierarchicalConsensusModules

Hierarchical consensus module identification in sampled data

plotColorUnderTree

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

Round numeric columns to given significant digits.

plotDendroAndColors

Dendrogram plot with color annotation of objects

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

Red and Green Color Image of Correlation Matrix

qvalue.restricted

qvalue convenience wrapper

signumAdjacencyFunction

Hard-thresholding adjacency function

standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable

standardScreeningNumericTrait

Standard screening for numeric traits

userListEnrichment

Measure enrichment between inputted and user-defined lists

recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data

sigmoidAdjacencyFunction

Sigmoid-type adacency function.

Signed eigengene-based connectivity

recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data

simpleConsensusCalculation

Simple calculation of a single consenus

Topological overlap for a subset of the whole set of genes

Colors this library uses for labeling modules.

Boxplot annotated by a Kruskal-Wallis p-value

simpleHierarchicalConsensusCalculation

Simple hierarchical consensus calculation

Scatterplot with density

standardScreeningBinaryTrait

Standard screening for binatry traits

Brain-Related Categories with Corresponding Gene Markers