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