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