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