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