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