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WGCNA (version 1.42)

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

11,673

Version

1.42

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

December 4th, 2014

Functions in WGCNA (1.42)

BrainRegionMarkers

Gene Markers for Regions of the Human Brain

blockwiseIndividualTOMs

Calculation of block-wise topological overlaps

conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.

Co-clustering measure of cluster preservation between two clusterings

consensusDissTOMandTree

Consensus clustering based on topological overlap and hierarchical clustering

moduleMergeUsingKME

Merge modules and reassign genes using kME.

Apply a function to elements of given multiData structures.

propVarExplained

Proportion of variance explained by eigengenes.

Iterative garbage collection.

intramodularConnectivity

Calculation of intramodular connectivity

Colors this library uses for labeling modules.

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

qvalue.restricted

qvalue convenience wrapper

lowerTri2matrix

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

Signed eigengene-based connectivity

Simulate a gene co-expression module

plotColorUnderTree

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

Estimate the true trait underlying a list of surrogate markers.

Consensus network (topological overlap).

Create a multiData structure.

Filter samples with too many missing entries across multiple data sets

coClustering.permutationTest

Permutation test for co-clustering

simulateEigengeneNetwork

Simulate eigengene network from a causal model

Constant-height tree cut

Filter genes with too many missing entries

populationMeansInAdmixture

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

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

keepCommonProbes

Keep probes that are shared among given data sets

Pairwise scatterplots of eigengenes

Label scatterplot points

blockwiseModules

Automatic network construction and module detection

networkScreeningGS

Network gene screening with an external gene significance measure

Biweight Midcorrelation

removePrincipalComponents

Remove leading principal components from data

labeledHeatmap.multiPage

Labeled heatmap divided into several separate plots.

Green-white-red color sequence

Show colors used to label modules

consensusProjectiveKMeans

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

corPredictionSuccess

Qunatification of success of gene screening

Meta-analysis of binary and continuous variables

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

Number of sets in a multi-set variable

Blood Cell Types with Corresponding Gene Markers

Add trait information to multi-set module eigengene structure

exportNetworkToCytoscape

Export network to Cytoscape

Generalized Topological Overlap Measure

coxRegressionResiduals

Deviance- and martingale residuals from a Cox regression model

Clustering coefficient calculation

hubGeneSignificance

Hubgene significance

proportionsInAdmixture

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

Inline display of progress

Inline display of progress

modulePreservation

Calculation of module preservation statistics

fixDataStructure

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

nearestNeighborConnectivityMS

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

networkConcepts

Calculations of network concepts

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

vectorizeMatrix

Turn a matrix into a vector of non-redundant components

Divide tasks among workers

Add grid lines to an existing plot.

mtd.setColnames

Get and set column names in a multiData structure.

userListEnrichment

Measure enrichment between inputted and user-defined lists

Number of present data entries.

TOMsimilarityFromExpr

Topological overlap matrix

setCorrelationPreservation

Summary correlation preservation measure

Red and Green Color Image of Correlation Matrix

pickSoftThreshold

Analysis of scale free topology for soft-thresholding

standardScreeningBinaryTrait

Standard screening for binatry traits

corPvalueFisher

Fisher's asymptotic p-value for correlation

standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable

Select one representative row per group

adjacency.splineReg

Calculate network adjacency based on natural cubic spline regression

Calculate overlap of modules

Space-less paste

chooseTopHubInEachModule

Chooses the top hub gene in each module

Relabel module labels to best match the given reference labels

multiData.eigengeneSignificance

Eigengene significance across multiple sets

recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data

dynamicMergeCut

Threshold for module merging

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation

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

standardScreeningNumericTrait

Standard screening for numeric traits

plotEigengeneNetworks

Eigengene network plot

Parallel quantile, median, mean

allowWGCNAThreads

Allow and disable multi-threading for certain WGCNA calculations

Topological overlap for a subset of a whole set of genes

Pad numbers with leading zeros to specified total width

Red and Green Color Specification

corPvalueStudent

Student asymptotic p-value for correlation

stratifiedBarplot

Bar plots of data across two splitting parameters

automaticNetworkScreening

One-step automatic network gene screening

cutreeStaticColor

Constant height tree cut using color labels

matrixToNetwork

Construct a network from a matrix

Basic Statistical Functions for Handling Missing Values

Standard error of the mean of a given vector.

Stem Cell-Related Genes with Corresponding Gene Markers

Filter genes with too many missing entries across multiple sets

goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries

plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples

consensusOrderMEs

Put close eigenvectors next to each other in several sets.

Graphical representation of the Topological Overlap Matrix

Break long character strings into multiple lines

Blue-white-red color sequence

Convert numerical labels to colors.

mergeCloseModules

Merge close modules in gene expression data

branchEigengeneDissim

Branch dissimilarity based on eigennodes (eigengenes).

signumAdjacencyFunction

Hard-thresholding adjacency function

Barplot with text or color labels.

Between and Within Group Sum of Squares Calculation

Set attributes on each component of a multiData structure

Red and Green Color Image of Data Matrix

accuracyMeasures

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

Weighted Gene Co-Expression Network Analysis

Calculation of biweight midcorrelations and associated p-values

GOenrichmentAnalysis

Calculation of GO enrichment (experimental)

mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information

Scatterplot with density

Produce a labeled heatmap plot

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

Prepend a comma to a non-empty string

recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data

relativeCorPredictionSuccess

Compare prediction success

consensusMEDissimilarity

Consensus dissimilarity of module eigengenes.

sigmoidAdjacencyFunction

Sigmoid-type adacency function.

simulateDatExpr

Simulation of expression data

Align expression data with given vector

moduleColor.getMEprefix

Get the prefix used to label module eigengenes.

branchSplitFromStabilityLabels

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

Meta-analysis Z statistic

Check adjacency matrix

Calculation of correlations and associated p-values

plotDendroAndColors

Dendrogram plot with color annotation of objects

verboseScatterplot

Scatterplot annotated by regression line and p-value

Calculate network adjacency

exportNetworkToVisANT

Export network data in format readable by VisANT

Fixed-height cut of a dendrogram.

Add error bars to a barplot.

branchSplit.dissim

Branch split based on dissimilarity.

Fast calculations of Pearson correlation.

conformityDecomposition

Conformity and module based decomposition of a network adjacency matrix.

Filter samples with too many missing entries

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

Visual check of scale-free topology

orderBranchesUsingHubGenes

Optimize dendrogram using branch swaps and reflections.

simulateSmallLayer

Simulate small modules

Green-black-red color sequence

adjacency.polyReg

Adjacency matrix based on polynomial regression

Shorten given character strings by truncating at a suitable separator.

Check structure and retrieve sizes of a group of datasets.

Determine whether the supplied object is a valid multiData structure

Removes the grey eigengene from a given collection of eigengenes.

Topological overlap for a subset of the whole set of genes

collapseRowsUsingKME

Selects one representative row per group based on kME

simulateMultiExpr

Simulate multi-set expression data

fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.

Apply a function to each set in a multiData structure.

moduleEigengenes

Calculate module eigengenes.

normalizeLabels

Transform numerical labels into normal order.

votingLinearPredictor

Voting linear predictor

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

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

simulateDatExpr5Modules

Simplified simulation of expression data

Boxplot annotated by a Kruskal-Wallis p-value

Calculate module eigengenes.

Color representation for a numeric variable

preservationNetworkConnectivity

Network preservation calculations

scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.

nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors

Put close eigenvectors next to each other

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

returnGeneSetsAsList

Return pre-defined gene lists in several biomedical categories.

swapTwoBranches

Select, swap, or reflect branches in a dendrogram.

networkScreening

Identification of genes related to a trait

unsignedAdjacency

Calculation of unsigned adjacency

Red-white-green color sequence

Opens a graphics window with specified dimensions

softConnectivity

Calculates connectivity of a weighted network.

Brain-Related Categories with Corresponding Gene Markers

Topological overlap matrix similarity and dissimilarity

Diagonal Discriminant Analysis

blockwiseConsensusModules

Find consensus modules across several datasets.

chooseOneHubInEachModule

Chooses a single hub gene in each module

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

correlationPreservation

Preservation of eigengene correlations

goodSamplesGenesMS

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

kMEcomparisonScatterplot

Function to plot kME values between two comparable data sets.

Union and intersection of multiple sets

overlapTableUsingKME

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

plotNetworkHeatmap

Network heatmap plot

plotModuleSignificance

Barplot of module significance

projectiveKMeans

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

ImmunePathwayLists

Immune Pathways with Corresponding Gene Markers

pickHardThreshold

Analysis of scale free topology for hard-thresholding.

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

Subset rows and columns in a multiData structure

nearestCentroidPredictor

Nearest centroid predictor

Rand index of two partitions

transposeBigData

Transpose a big matrix or data frame