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WGCNA (version 1.00)

Weighted Gene Co-Expression Network Analysis

Description

Functions necessary to perform Weighted Gene Co-Expression Network Analysis

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Version

Install

install.packages('WGCNA')

Monthly Downloads

13,041

Version

1.00

License

GPL (>= 2)

Maintainer

Peter Langfelder

Last Published

February 15th, 2011

Functions in WGCNA (1.00)

sigmoidAdjacencyFunction

Sigmoid-type adacency function.

orderMEs

Put close eigenvectors next to each other

GTOMdist

Generalized Topological Overlap Measure

alignExpr

Align expression data with given vector

cutreeStaticColor

Constant height tree cut using color labels

bicor

Biweight Midcorrelation

greenWhiteRed

Green-white-red color sequence

simulateModule

Simulate a gene co-expression module

addGuideLines

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

automaticNetworkScreeningGS

One-step automatic network gene screening with external gene significance

labeledBarplot

Barplot with text or color labels.

colQuantileC

Fast colunm-wise quantile of a matrix.

addErrorBars

Add error bars to a barplot.

corAndPvalue

Calculation of correlations and associated p-values

TOMsimilarityFromExpr

Topological overlap matrix

moduleColor.getMEprefix

Get the prefix used to label module eigengenes.

corPvalueStudent

Student asymptotic p-value for correlation

multiSetMEs

Calculate module eigengenes.

addGrid

Add grid lines to an existing plot.

relativeCorPredictionSuccess

Compare prediction success

labeledHeatmap

Produce a labeled heatmap plot

removeGreyME

Removes the grey eigengene from a given collection of eigengenes.

networkConcepts

Calculations of network concepts

unsignedAdjacency

Calculation of unsigned adjacency

blockwiseConsensusModules

Find consensus modules across several datasets.

moduleNumber

Fixed-height cut of a dendrogram.

propVarExplained

Proportion of variance explained by eigengenes.

plotEigengeneNetworks

Eigengene network plot

signumAdjacencyFunction

Hard-thresholding adjacency function

automaticNetworkScreening

One-step automatic network gene screening

collapseRows

Select one representative row per group

conformityBasedNetworkConcepts

Calculation of conformity-based network concepts.

goodSamplesMS

Filter samples with too many missing entries across multiple data sets

prepComma

Prepend a comma to a non-empty string

consensusMEDissimilarity

addTraitToMEs

Add trait information to multi-set module eigengene structure

pickSoftThreshold

Analysis of scale free topology for soft-thresholding

subsetTOM

Topological overlap for a subset of a whole set of genes

TOMplot

Graphical representation of the Topological Overlap Matrix

dynamicMergeCut

Threshold for module merging

standardScreeningBinaryTrait

Standard screening for binatry traits

blockwiseModules

Automatic network construction and module detection

plotDendroAndColors

Dendrogram plot with color annotation of objects

mergeCloseModules

Merge close modules in gene expression data

simulateMultiExpr

Simulate multi-set expression data

stat.bwss

Between and Within Group Sum of Squares Calculation

exportNetworkToCytoscape

Export network to Cytoscape

nPresent

Number of present data entries.

bicorAndPvalue

Calculation of biweight midcorrelations and associated p-values

goodSamplesGenesMS

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

intramodularConnectivity

Calculation of intramodular connectivity

nearestNeighborConnectivity

Connectivity to a constant number of nearest neighbors

goodGenesMS

Filter genes with too many missing entries across multiple sets

overlapTable

Calculate overlap of modules

recutConsensusTrees

Repeat blockwise consensus module detection from pre-calculated data

checkSets

Check structure and retrieve sizes of a group of datasets.

cutreeStatic

Constant-height tree cut

goodGenes

Filter genes with too many missing entries

numbers2colors

Color representation for a numeric variable

plotNetworkHeatmap

Network heatmap plot

scaleFreeFitIndex

Calculation of fitting statistics for evaluating scale free topology fit.

consensusProjectiveKMeans

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

standardScreeningNumericTrait

Standard screening for numeric traits

keepCommonProbes

Keep probes that are shared among given data sets

sizeGrWindow

Opens a graphics window with specified dimensions

plotClusterTreeSamples

Annotated clustering dendrogram of microarray samples

pquantile

Parallel quantile, median, mean

greenBlackRed

Green-black-red color sequence

verboseBarplot

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

exportNetworkToVisANT

Export network data in format readable by VisANT

Qunatification of success of gene screening

projectiveKMeans

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

GOenrichmentAnalysis

Calculation of GO enrichment (experimental)

corPvalueFisher

Fisher's asymptotic p-value for correlation

correlationPreservation

Preservation of eigengene correlations

displayColors

Show colors used to label modules

Inline display of progress

goodSamples

Filter samples with too many missing entries

mutualInfoAdjacency

Calculate weighted adjacency matrices based on mutual information

randIndex

Rand index of two partitions

vectorizeMatrix

Turn a matrix into a vector of non-redundant components

modulePreservation

Calculation of module preservation statistics

WGCNA-package

Weighted Gene Co-Expression Network Analysis

matchLabels

Relabel module labels to best match the given reference labels

stat.diag.da

Diagonal Discriminant Analysis

preservationNetworkConnectivity

Network preservation calculations

plotMEpairs

Pairwise scatterplots of eigengenes

fundamentalNetworkConcepts

Calculation of fundamental network concepts from an adjacency matrix.

normalizeLabels

Transform numerical labels into normal order.

Basic Statistical Functions for Handling Missing Values

simulateDatExpr

Simulation of expression data

networkScreeningGS

Network gene screening with an external gene significance measure

plot.cor

Red and Green Color Image of Correlation Matrix

labels2colors

Convert numerical labels to colors.

fixDataStructure

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

recutBlockwiseTrees

Repeat blockwise module detection from pre-calculated data

collectGarbage

Iterative garbage collection.

simulateDatExpr5Modules

Simplified simulation of expression data

scaleFreePlot

Visual check of scale-free topology

cor

Fast calculations of Pearson correlation.

redWhiteGreen

Red-white-green color sequence

consensusOrderMEs

Put close eigenvectors next to each other in several sets.

setCorrelationPreservation

Summary correlation preservation measure

checkAdjMat

Check adjacency matrix

standardScreeningCensoredTime

Standard Screening with regard to a Censored Time Variable

verboseScatterplot

Scatterplot annotated by regression line and p-value

verboseBoxplot

Boxplot annotated by a Kruskal-Wallis p-value

simulateEigengeneNetwork

Simulate eigengene network from a causal model

goodSamplesGenes

Iterative filtering of samples and genes with too many missing entries

adjacency

Calculate network adjacency

labelPoints

Label scatterplot points

plotColorUnderTree

Plot color rows under a dendrogram

standardColors

Colors this library uses for labeling modules.

simulateSmallLayer

Simulate small modules

metaZfunction

Meta-analysis Z statistic

softConnectivity

Calculates connectivity of a weighted network.

pickHardThreshold

Analysis of scale free topology for hard-thresholding.

moduleEigengenes

Calculate module eigengenes.

plot.mat

Red and Green Color Image of Data Matrix

plotModuleSignificance

Barplot of module significance

signedKME

Signed eigengene-based connectivity

stdErr

Standard error of the mean of a given vector.

vectorTOM

Topological overlap for a subset of the whole set of genes

clusterCoef

Clustering coefficient calculation

nearestNeighborConnectivityMS

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

rankPvalue

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

AUV2predicted

Prediction of Weighted Mutual Information Adjacency Matrix by Correlation

networkScreening

Identification of genes related to a trait

rgcolors.func

Red and Green Color Specification