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