Package: scGraphVerse 1.3.0

Francesco Cecere

scGraphVerse: scGraphVerse: A Gene Network Analysis Package

A package for inferring, comparing, and visualizing gene networks from single-cell RNA sequencing data. It integrates multiple methods (GENIE3, GRNBoost2, ZILGM, PCzinb, and JRF) for robust network inference, supports consensus building across methods or datasets, and provides tools for evaluating regulatory structure and community similarity. GRNBoost2 requires Python package 'arboreto' which can be installed using init_py(install_missing = TRUE). This package includes adapted functions from ZILGM (Park et al., 2021), JRF (Petralia et al., 2015), and learn2count (Nguyen et al. 2023) packages with proper attribution under GPL-2 license.

Authors:Francesco Cecere [aut, cre], Annamaria Carissimo [aut], Daniela De Canditiis [aut], Claudia Angelini [aut, fnd]

scGraphVerse_1.3.0.tar.gz
scGraphVerse_1.3.0.zip(r-4.7)scGraphVerse_1.3.0.zip(r-4.6)scGraphVerse_1.3.0.zip(r-4.5)
scGraphVerse_1.3.0.tgz(r-4.6-x86_64)scGraphVerse_1.3.0.tgz(r-4.6-arm64)scGraphVerse_1.3.0.tgz(r-4.5-x86_64)scGraphVerse_1.3.0.tgz(r-4.5-arm64)
scGraphVerse_1.3.0.tar.gz(r-4.7-arm64)scGraphVerse_1.3.0.tar.gz(r-4.7-x86_64)scGraphVerse_1.3.0.tar.gz(r-4.6-arm64)scGraphVerse_1.3.0.tar.gz(r-4.6-x86_64)
scGraphVerse_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scGraphVerse/json (API)

# Install 'scGraphVerse' in R:
install.packages('scGraphVerse', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ngsfc/scgraphverse/issues

Pkgdown/docs site:https://ngsfc.github.io

Datasets:

On BioConductor:scGraphVerse-1.3.0(bioc 3.24)scGraphVerse-1.2.0(bioc 3.23)

generegulationnetworkinferencesinglecellrnaseqvisualizationsoftwaregraphandnetworkgenesetenrichmentnetworkenrichmentpathwayssequencingreactomenetworkkegg

5.08 score 1 stars 4 scripts 192 downloads 26 exports 94 dependencies

Last updated from:9153b37355. Checks:1 WARNING, 7 NOTE, 4 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING438
linux-devel-arm64NOTE954
linux-devel-x86_64ERROR1062
source / vignettesOK868
linux-release-arm64NOTE970
linux-release-x86_64NOTE1277
macos-release-arm64NOTE726
macos-release-x86_64NOTE1134
macos-oldrel-arm64NOTE743
macos-oldrel-x86_64NOTE958
windows-develERROR1479
windows-releaseERROR1701
windows-oldrelERROR1721
wasm-releaseOK368

Exports:build_network_seclassify_edgescommunity_pathcommunity_similaritycompare_consensuscompute_community_metricscompute_topology_metricscreate_consensuscreate_maecutoff_adjacencydownload_Atlasearlyjedge_mininggenerate_adjacencyinfer_networksinit_pyPCzinbplot_community_comparisonplot_network_comparisonplotgplotROCpscoresselgenestringdb_adjacencysymmetrizezinb_simdata

Dependencies:abindaskpassBHBiobaseBiocBaseUtilsBiocGenericsBiocParallelbstclicodetoolscpp11curlDelayedArraydigestdistributions3doParalleldoRNGdplyrfarverforeachformatRfutile.loggerfutile.optionsgbmgenericsGENIE3GenomicRangesggplot2glmnetgluegraphgtableherehttrigraphIRangesisobanditeratorsjsonlitelabelinglambda.rlatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmimempathMultiAssayExperimentnumDerivopensslpillarpkgconfigplyrpngpsclpurrrR6rappdirsRColorBrewerRcppRcppEigenRcppTOMLreshape2reticulaterlangrngtoolsrpartrprojrootS4ArraysS4VectorsS7scalesSeqinfoshapeSingleCellExperimentsnowSparseArraystringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselectutf8vctrsviridisLiteWeightSVMwithrXVector

scGraphVerse Case Study: B-cell GRN Reconstruction
Introduction | 1. Dataset and Preprocessing | 2. Network Inference | 2.1. Building Adjacency Matrices | 3. Consensus and Community Detection | 4. Validation with STRINGdb | 5. Conclusion | Session Information
Rendered fromcase_study.Rmdusingknitr::rmarkdown

Last update: 2025-10-12
Started: 2025-05-05

scGraphVerse Case Study: Zero-Inflated Simulation and GRN Inference
Introduction | Why use scGraphVerse? | How scGraphVerse works | Simulation study | 1. Load Ground-Truth Network | 2. Simulating Zero-Inflated Count Data | 3. Inferring Networks with GENIE3 | 4. ROC Curve and AUC | 4.1. Precision–Recall and Graph Visualization | 5. Consensus Networks and Community Similarity | 5.1. Edge Mining
Rendered fromsimulation_study.Rmdusingknitr::rmarkdown

Last update: 2025-10-12
Started: 2025-05-05

Readme and manuals

Help Manual

Help pageTopics
Create a SummarizedExperiment for Network Storagebuild_network_se
Classify Edges as TP, FP, or FNclassify_edges
Community Detection and Pathway Enrichment Analysiscommunity_path
Compare Community Assignments and Topological Propertiescommunity_similarity
Compare Consensus and Reference Graphs or STRINGdb Networkscompare_consensus
Compute Community Assignment Similarity Metricscompute_community_metrics
Compute Network Topological Propertiescompute_topology_metrics
Create a Consensus Adjacency Matrix from Multiple Networkscreate_consensus
Create MultiAssayExperiment from Multiple Single-Cell Datasetscreate_mae
Threshold Adjacency Matrices Based on Shuffled Network Quantilescutoff_adjacency
Download and Load an RDS File from a URLdownload_Atlas
Modify Cell Names and Combine Datasetsearlyj
Edge Mining of Gene Interactions Using PubMededge_mining
Generate Adjacency Matrices from Gene Interaction Tablesgenerate_adjacency
Infer Gene Regulatory Networks from Expression Matricesinfer_networks
Initialize Python Environment for GRNBoost2init_py
Structure learning for count data using PC algorithmsPCzinb
Visualize Community and Topology Comparisonplot_community_comparison
Visualize Network Comparisonplot_network_comparison
Visualize Graphs from Adjacency Matricesplotg
Plot ROC Curves for Inferred NetworksplotROC
Compute Performance Scores for Predicted Adjacency Matricespscores
Select Top Expressed Genes from Single-Cell Dataselgene
Build Adjacency Matrices for Physical Interactions from STRING (POST API)stringdb_adjacency
Symmetrize Adjacency Matrices in a SummarizedExperimentsymmetrize
Toy adjacency matrix for examplestoy_adj_matrix
Toy MultiAssayExperiment for Network Inferencetoy_counts
Simulate Zero-Inflated Negative Binomial (ZINB) Count Matrices with Sequencing Depthzinb_simdata