Package index
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alsData - Amyotrophic Lateral Sclerosis (ALS) dataset
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ancestors()descendants()parents()siblings() - Node ancestry utilities
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clusterGraph() - Topological graph clustering
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clusterScore() - Module scoring
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colorGraph() - Vertex and edge graph coloring on the base of fitting
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cplot() - Subgraph mapping
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dagitty2graph() - Graph conversion from dagitty to igraph
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extractClusters() - Cluster extraction utility
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factor.analysis() - Factor analysis for high dimensional data
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gplot() - Graph plotting with renderGraph
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graph2dag() - Convert directed graphs to directed acyclic graphs (DAGs)
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graph2dagitty() - Graph conversion from igraph to dagitty
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graph2lavaan() - Graph to lavaan model
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kegg.pathways - KEGG pathways
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kegg - KEGG interactome
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lavaan2graph() - lavaan model to graph
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loadPathways() - Import pathways and generate a reference network
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localCI.test() - Conditional Independence (CI) local tests of an acyclic graph
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mergeNodes() - Graph nodes merging by a membership attribute
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modelSearch() - Optimal model search strategies
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orientEdges() - Assign edge orientation of an undirected graph
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pairwiseMatrix() - Pairwise plotting of multivariate data
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parameterEstimates() - Parameter Estimates of a fitted SEM
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pathFinder() - Perturbed path search utility
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properties() - Graph properties summary and graph decomposition
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resizeGraph() - Interactome-assisted graph re-seizing
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sachs - Sachs multiparameter flow cytometry data and consensus model
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SEMace() - Compute the Average Causal Effect (ACE) for a given source-sink pair
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SEMbap() - Bow-free covariance search and data de-correlation
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SEMdag() - Estimate a DAG from an input (or empty) graph
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SEMdci() - SEM-based differential network analysis
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SEMgsa() - SEM-based gene set analysis
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SEMpath() - Search for directed or shortest paths between pairs of source-sink nodes
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SEMrun() - Fit a graph as a Structural Equation Model (SEM)
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SEMtree() - Tree-based structure learning methods
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Shipley.test() - Missing edge testing implied by a DAG with Shipley's basis-set
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summary(<GGM>) - GGM model summary
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summary(<RICF>) - RICF model summary
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transformData() - Transform data methods
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weightGraph() - Graph weighting methods