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