Divide tasks among workers
Brain-Related Categories with Corresponding Gene Markers
Graphical representation of the Topological Overlap Matrix
Blood Cell Types with Corresponding Gene Markers
Topological overlap matrix similarity and dissimilarity
Branch split.
Allow and disable multi-threading for certain WGCNA calculations
automaticNetworkScreening
One-step automatic network gene screening
Branch split based on dissimilarity.
Attempt to calculate an appropriate block size to maximize efficiency of block-wise calcualtions.
Check structure and retrieve sizes of a group of datasets.
blockwiseConsensusModules
Find consensus modules across several datasets.
Generalized Topological Overlap Measure
Immune Pathways with Corresponding Gene Markers
branchSplitFromStabilityLabels
Branch split (dissimilarity) statistics derived from labels determined from a stability study
Add grid lines to an existing plot.
Chooses a single hub gene in each module
Check adjacency matrix
Calculation of a (single) consenus with optional data calibration.
Consensus clustering based on topological overlap and hierarchical clustering
Prediction of Weighted Mutual Information Adjacency Matrix by Correlation
Selects one representative row per group based on kME
Various basic operations on BlockwiseData
objects.
Add vertical ``guide lines'' to a dendrogram plot
Add trait information to multi-set module eigengene structure
Calculate network adjacency
Iterative garbage collection.
Fast calculations of Pearson correlation.
binarizeCategoricalColumns
Turn categorical columns into sets of binary indicators
Adjacency matrix based on polynomial regression
binarizeCategoricalVariable
Turn a categorical variable into a set of binary indicators
Calculation of correlations and associated p-values
Calculate network adjacency based on natural cubic spline regression
Fast colunm- and row-wise quantile of a matrix.
Student asymptotic p-value for correlation
Calculation of block-wise topological overlaps
Deviance- and martingale residuals from a Cox regression model
Preservation of eigengene correlations
Constant-height tree cut
Consensus dissimilarity of module eigengenes.
Select one representative row per group
Calculate consensus kME (eigengene-based connectivities) across multiple data sets.
Break long character strings into multiple lines
Threshold for module merging
fundamentalNetworkConcepts
Calculation of fundamental network concepts from an adjacency matrix.
Consensus selection of group representatives
Automatic network construction and module detection
Empirical Bayes-moderated adjustment for unwanted covariates
Hubgene significance
Impute missing data separately in each module
Co-clustering measure of cluster preservation between two clusterings
Accuracy measures for a 2x2 confusion matrix or for vectors of predicted and observed values.
Consensus network (topological overlap).
Label scatterplot points
Calculation of hierarchical consensus topological overlap matrix
hierarchicalMergeCloseModules
Merge close (similar) hierarchical consensus modules
Convert numerical labels to colors.
Gene Markers for Regions of the Human Brain
Barplot with text or color labels.
Fast joint calculation of row- or column-wise minima and indices of minimum elements
coClustering.permutationTest
Permutation test for co-clustering
Put close eigenvectors next to each other in several sets.
Add error bars to a barplot.
Convert a list to a multiData structure and vice-versa.
Calculation of GO enrichment (experimental)
automaticNetworkScreeningGS
One-step automatic network gene screening with external gene significance
Construct a network from a matrix
Fixed-height cut of a dendrogram.
Merge close modules in gene expression data
Calculation of module preservation statistics
Biweight Midcorrelation
Topological overlap matrix
Iterative filtering of samples and genes with too many missing entries across multiple data sets
Number of sets in a multi-set variable
Get the prefix used to label module eigengenes.
consensusProjectiveKMeans
Consensus projective K-means (pre-)clustering of expression data
Nearest centroid predictor
Calculate module eigengenes.
Estimate the true trait underlying a list of surrogate markers.
factorizeNonNumericColumns
Turn non-numeric columns into factors
Qunatification of success of gene screening
Filter samples with too many missing entries across multiple data sets
Fisher's asymptotic p-value for correlation
Create, merge and expand BlockwiseData objects
Put single-set data into a form useful for multiset calculations.
Union and intersection of multiple sets
Filter samples with too many missing entries
Export network to Cytoscape
Create a list holding consensus calculation options.
hierarchicalConsensusMEDissimilarity
Hierarchical consensus calculation of module eigengene dissimilarity
Iterative filtering of samples and genes with too many missing entries
Calculation of intramodular connectivity
Determine whether the supplied object is a valid multiData structure
Export network data in format readable by VisANT
Color representation for a numeric variable
Green-black-red color sequence
Calculation of biweight midcorrelations and associated p-values
Network gene screening with an external gene significance measure
hierarchicalConsensusModules
Hierarchical consensus network construction and module identification
Create a list holding information about dividing data into blocks
Function to plot kME values between two comparable data sets.
Green-white-red color sequence
Calculate overlap of modules
Calculate individual correlation network matrices
Red and Green Color Image of Correlation Matrix
orderBranchesUsingHubGenes
Optimize dendrogram using branch swaps and reflections.
Keep probes that are shared among given data sets
Branch dissimilarity based on eigennodes (eigengenes).
Weights used in biweight midcovariance
Blue-white-red color sequence
Reconstruct a symmetric matrix from a distance (lower-triangular) representation
Determines significant overlap between modules in two networks based on kME tables.
populationMeansInAdmixture
Estimate the population-specific mean values in an admixed population.
Relabel module labels to best match the given reference labels
Dendrogram plot with color annotation of objects
Inline display of progress
Inline display of progress
Apply a function to each set in a multiData structure.
Proportion of variance explained by eigengenes.
Chooses the top hub gene in each module
Estimate the proportion of pure populations in an admixed population based on marker expression
values.
Calculate module eigengenes.
Clustering coefficient calculation
Merge modules and reassign genes using kME.
Turn a multiData structure into a single matrix or data frame.
Subset rows and columns in a multiData structure
conformityBasedNetworkConcepts
Calculation of conformity-based network concepts.
Create a multiData structure.
Conformity and module based decomposition of a network adjacency matrix.
Set attributes on each component of a multiData structure
Red-white-green color sequence
Get all elementary inputs in a consensus tree
relativeCorPredictionSuccess
Compare prediction success
Calculate weighted adjacency matrices based on mutual information
Number of present data entries.
Parallel quantile, median, mean
pruneAndMergeConsensusModules
Iterative pruning and merging of (hierarchical) consensus modules
Prune (hierarchical) consensus modules by removing genes with low eigengene-based intramodular connectivity
Removes the grey eigengene from a given collection of eigengenes.
multiData.eigengeneSignificance
Eigengene significance across multiple sets
Apply a function to elements of given multiData structures.
convertNumericColumnsToNumeric
Convert character columns that represent numbers to numeric
Constant height tree cut using color labels
Red and Green Color Specification
Show colors used to label modules
Blockwise module identification in sampled data
Analogs of grep(l) and (g)sub for multiple patterns and relacements
Simulate multi-set expression data
removePrincipalComponents
Remove leading principal components from data
Simulate small modules
standardScreeningBinaryTrait
Standard screening for binatry traits
Create a new consensus tree
standardScreeningCensoredTime
Standard Screening with regard to a Censored Time Variable
Calculation of unsigned adjacency
Filter genes with too many missing entries
Measure enrichment between inputted and user-defined lists
Creates a list of correlation options.
Filter genes with too many missing entries across multiple sets
Put close eigenvectors next to each other
orderMEsByHierarchicalConsensus
Order module eigengenes by their hierarchical consensus similarity
simpleConsensusCalculation
Simple calculation of a single consenus
hierarchicalConsensusCalculation
Hierarchical consensus calculation
Analysis of scale free topology for hard-thresholding.
Eigengene network plot
Analysis of scale free topology for soft-thresholding
simpleHierarchicalConsensusCalculation
Simple hierarchical consensus calculation
Barplot of module significance
Red and Green Color Image of Data Matrix
Estimate the q-values for a given set of p-values
Calculation of measures of fuzzy module membership (KME) in hierarchical consensus modules
Calculations of network concepts
Identification of genes related to a trait
Produce a labeled heatmap plot
Labeled heatmap divided into several separate plots.
Pairwise scatterplots of eigengenes
Meta-analysis of binary and continuous variables
Prepend a comma to a non-empty string
Pad numbers with leading zeros to specified total width
standardScreeningNumericTrait
Standard screening for numeric traits
Get and set column names in a multiData structure.
Meta-analysis Z statistic
Repeat blockwise module detection from pre-calculated data
Standard error of the mean of a given vector.
Repeat blockwise consensus module detection from pre-calculated data
Visual check of scale-free topology
Select, swap, or reflect branches in a dendrogram.
qvalue convenience wrapper
Transpose a big matrix or data frame
Rand index of two partitions
If possible, simplify a multiData structure to a 3-dimensional array.
Estimate the p-value for ranking consistently high (or low) on multiple lists
nearestNeighborConnectivity
Connectivity to a constant number of nearest neighbors
nearestNeighborConnectivityMS
Connectivity to a constant number of nearest neighbors across multiple data sets
selectFewestConsensusMissing
Select columns with the lowest consensus number of missing data
Round numeric columns to given significant digits.
setCorrelationPreservation
Summary correlation preservation measure
Hard-thresholding adjacency function
Bar plots of data across two splitting parameters
Replace missing values with a constant.
Shorten given character strings by truncating at a suitable separator.
Simulation of expression data
Return pre-defined gene lists in several biomedical categories.
Topological overlap for a subset of a whole set of genes
sampledHierarchicalConsensusModules
Hierarchical consensus module identification in sampled data
Simplified simulation of expression data
Barplot with error bars, annotated by Kruskal-Wallis or ANOVA p-value
Calculation of fitting statistics for evaluating scale free topology fit.
Opens a graphics window with specified dimensions
Calculates connectivity of a weighted network.
Boxplot annotated by a Kruskal-Wallis p-value
Create a list of network construction arguments (options).
Topological overlap for a subset of the whole set of genes
Transform numerical labels into normal order.
Annotated clustering dendrogram of microarray samples
Plot color rows in a given order, for example under a dendrogram
Plot multiple histograms in a single plot
Turn a matrix into a vector of non-redundant components
Network heatmap plot
preservationNetworkConnectivity
Network preservation calculations
Projective K-means (pre-)clustering of expression data
Sigmoid-type adacency function.
Signed eigengene-based connectivity
Simulate eigengene network from a causal model
Simulate a gene co-expression module
Space-less paste
Colors this library uses for labeling modules.
Scatterplot with density
Scatterplot annotated by regression line and p-value
Voting linear predictor
Pathways with Corresponding Gene Markers - Compiled by Mike Palazzolo and Jim Wang from CHDI
Stem Cell-Related Genes with Corresponding Gene Markers
Align expression data with given vector