scGraphVerse: A Gene Regulatory Network Analysis Package

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Documentation for package ‘scGraphVerse’ version 0.99.19

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build_network_se Create a SummarizedExperiment for Network Storage
classify_edges Classify Edges as TP, FP, or FN
community_path Community Detection and Pathway Enrichment Analysis
community_similarity Compare Community Assignments and Topological Properties
compare_consensus Compare Consensus and Reference Graphs or STRINGdb Networks
compute_community_metrics Compute Community Assignment Similarity Metrics
compute_topology_metrics Compute Network Topological Properties
create_consensus Create a Consensus Adjacency Matrix from Multiple Networks
create_mae Create MultiAssayExperiment from Multiple Single-Cell Datasets
cutoff_adjacency Threshold Adjacency Matrices Based on Shuffled Network Quantiles
download_Atlas Download and Load an RDS File from a URL
earlyj Modify Cell Names and Combine Datasets
edge_mining Edge Mining of Gene Interactions Using PubMed
generate_adjacency Generate Adjacency Matrices from Gene Interaction Tables
infer_networks Infer Gene Regulatory Networks from Expression Matrices
init_py Initialize Python Environment for GRNBoost2
PCzinb Structure learning for count data using PC algorithms
plotg Visualize Graphs from Adjacency Matrices
plotROC Plot ROC Curves for Inferred Networks
plot_community_comparison Visualize Community and Topology Comparison
plot_network_comparison Visualize Network Comparison
pscores Compute Performance Scores for Predicted Adjacency Matrices
selgene Select Top Expressed Genes from Single-Cell Data
stringdb_adjacency Build Adjacency Matrices for Physical Interactions from STRING (POST API)
symmetrize Symmetrize Adjacency Matrices in a SummarizedExperiment
toy_adj_matrix Toy adjacency matrix for examples
toy_counts Toy MultiAssayExperiment for Network Inference
zinb_simdata Simulate Zero-Inflated Negative Binomial (ZINB) Count Matrices with Sequencing Depth