Package: NOVA 1.0.0

NOVA: Network Of Versatile Cell-Cell Communication Analysis

NOVA (Network Of Versatile cell-cell Analysis) is a high-performance R package for predicting and visualizing cell-to-cell communication networks from single-cell and bulk transcriptomic data. It leverages connectomeDB2020, the most comprehensive manually curated ligand-receptor interaction database, to identify signaling interactions between cell types. NOVA features vectorized computations, parallel processing, and seamless integration with Seurat (V4/V5) for efficient analysis of large-scale datasets.

Authors:Zaoqu Liu [aut, cre]

NOVA_1.0.0.tar.gz
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NOVA_1.0.0.tgz(r-4.6-x86_64)NOVA_1.0.0.tgz(r-4.6-arm64)NOVA_1.0.0.tgz(r-4.5-x86_64)NOVA_1.0.0.tgz(r-4.5-arm64)
NOVA_1.0.0.tar.gz(r-4.7-arm64)NOVA_1.0.0.tar.gz(r-4.7-x86_64)NOVA_1.0.0.tar.gz(r-4.6-arm64)NOVA_1.0.0.tar.gz(r-4.6-x86_64)
NOVA_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
NOVA/json (API)

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

Bug tracker:https://github.com/zaoqu-liu/nova/issues

Pkgdown/docs site:https://zaoqu-liu.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

3.73 score 1 stars 18 scripts 450 downloads 34 exports 76 dependencies

Last updated from:be0787f275 (on main). Checks:11 WARNING, 2 OK. Indexed: no.

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linux-devel-x86_64WARNING260
source / vignettesOK316
linux-release-arm64WARNING237
linux-release-x86_64WARNING219
macos-release-arm64WARNING133
macos-release-x86_64WARNING262
macos-oldrel-arm64WARNING139
macos-oldrel-x86_64WARNING302
windows-develWARNING174
windows-releaseWARNING202
windows-oldrelWARNING202
wasm-releaseOK191

Exports:.export_lr_pairsAddNOVAResultsConvertGeneSymbolsConvertIDsToSymbolsDiffEdgesExportDiffExportLRPairsExportResultsExtractEdgesFilterEdgesGetCellMetadataGetClustersGetEdgesGetExpressionMatrixGetHomologyMappingGetLRDatabasenova_palettePlotBubblePlotChordPlotCircosPlotClusterComparisonPlotDiffHeatmapPlotDotPlotPlotHeatmapPlotLRNetworkPlotLRPairsPlotNetworkPlotVolcanoSavePlotSeuratToNOVASummarizeByClusterSummarizeByLRsupported_id_typessupported_species

Dependencies:base64encBiocGenericscachemcirclizecliclueclustercodetoolscolorspaceComplexHeatmapcpp11crayondata.tabledigestdoParalleldplyrfarverfastmapforeachfuturefuture.applygenericsGetoptLongggforceggplot2ggraphggrepelGlobalOptionsglobalsgluegraphlayoutsgridExtragtableigraphIRangesisobanditeratorsjsonlitelabelinglatticelifecyclelistenvmagrittrMASSMatrixmatrixStatsmemoiseparallellypillarpkgconfigpngpolyclippurrrR6RColorBrewerRcppRcppArmadillorjsonrlangS4VectorsS7scalesshapestringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithr

Advanced Usage
Introduction | Setup | Performance Optimization | Parallel Processing | NOVA Options | Memory Efficiency | Custom Ligand-Receptor Database | Creating Custom Database | Using Custom Database | Extending Built-in Database | Filtering and Subsetting | Advanced Filtering | Subsetting by Cluster | Programmatic Workflows | Batch Processing | Custom Analysis Pipeline | Integration with Other Tools | Export for Cytoscape | Integration with CellChat/LIANA | Troubleshooting | Common Issues | Session Info | Author
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Last update: 2026-01-26
Started: 2026-01-26

Algorithm & Methodology
Overview | Theoretical Background | Cell-Cell Communication | Mathematical Framework | 1. Gene Expression Statistics | Detection Rate (Percentage of Expressing Cells) | Mean Expression | 2. Expression Specificity | 3. Edge Weight Calculation | Expression-based Weight | Specificity-based Weight | 4. Filtering Criteria | Algorithmic Implementation | Cluster Statistics Computation | Edge Computation | Differential Analysis | Fold Change Calculation | Delta Metrics | Ligand-Receptor Database | connectomeDB2020 | Database Structure | Multi-Species Support | Homology Mapping | Supported Species | Computational Efficiency | Vectorization Strategy | Complexity Analysis | References | Author
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Differential Communication Analysis
Introduction | Setup | Simulating Two Conditions | Running Individual Analyses | Differential Analysis | Running DiffEdges | Understanding the Output | Visualization | Differential Heatmap | Volcano Plot | Summarization Functions | By Cluster Pair | By LR Pair | Filtering Significant Changes | Interpreting Results | Key Metrics | Biological Interpretation | Exporting Results | Best Practices | 1. Sample Matching | 2. Multiple Testing Consideration | 3. Biological Validation | Session Info | Author
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Getting Started with NOVA
Introduction | Key Features | Installation | Quick Start | Loading the Package | Simulating Example Data | Loading LR Database | Running NOVA Analysis | Exploring Results | Working with Seurat Objects | Basic Visualization | Communication Heatmap | Network Graph | Session Info | Author | Citation
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Multi-Species Analysis
Introduction | Supported Species | Species Details | Homology Mapping | How It Works | Converting Gene Symbols | Analyzing Mouse Data | Standard Workflow | Cross-Species Comparison | Comparative Study Design | Gene ID Types | Converting Between ID Types | Special Considerations | 1. One-to-Many Mappings | 2. Missing Orthologs | 3. Species-Specific Genes | Best Practices | Workflow Recommendations | Quality Control | Session Info | Author
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Visualization Gallery
Introduction | Setup | Creating Example Data | Running Analysis | 1. Communication Heatmap | Basic Heatmap | Specificity-weighted Heatmap | 2. Network Visualization | Circular Layout | Force-directed Layout | Kamada-Kawai Layout | 3. Chord Diagram | Specificity-based Chord | 4. Ligand-Receptor Pairs Visualization | 5. Color Palette | 6. Custom Styling | Custom Colors | 7. Saving Plots | Summary Table | Session Info | Author
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Last update: 2026-01-26
Started: 2026-01-26