Package: fastCNV 2.0.0

fastCNV: Fast CNV Detection for Single-Cell and Spatial Transcriptomics

Fast and accurate detection of Copy Number Variations (CNVs) in single-cell RNA sequencing (scRNA-seq) and Spatial Transcriptomics (ST) data, including 10X Visium and Visium HD. Provides sliding window-based CNV inference, hierarchical clustering of CNV profiles, and publication-ready visualization. Compatible with Seurat 4.x/5.x.

Authors:Zaoqu Liu [cre, aut], Gadea Cabrejas [aut, cph], Clarice Groeneveld [aut]

fastCNV_2.0.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fastCNV/json (API)

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

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

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

Datasets:

On CRAN:

Conda:

3.34 score 1 stars 11 scripts 20 exports 200 dependencies

Last updated from:f61d061cd3 (on main). Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING354
source / vignettesOK308
linux-release-x86_64WARNING365
macos-release-arm64WARNING182
macos-oldrel-arm64WARNING198
windows-develWARNING310
windows-releaseWARNING307
windows-oldrelWARNING297
wasm-releaseOK207

Exports:annotateCNVTreeannotations8umTo16umbuildCNVTreeclassifyCNVCNVAnalysisCNVCallingCNVCallingListCNVClassificationCNVClusterCNVPerChromosomeArmCNVTreefastCNVfastCNV_10XHDgenerateCNVClonesMatrixgetGenesmergeCNVClustersplotCNVResultsplotCNVResultsHDplotCNVTreeprepareCountsForCNVAnalysis

Dependencies:abindAnnotationDbiapeaplotaskpassbase64encBHBiobaseBiocFileCacheBiocGenericsbiomaRtBiostringsbitbit64bitopsblobbslibcachemcaToolscirclizecliclueclustercodetoolscolorspacecommonmarkComplexHeatmapcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrdeldirdigestdoParalleldotCall64dplyrdqrngevaluatefarverfastDummiesfastmapfastmatchfilelockfitdistrplusFNNfontawesomefontBitstreamVerafontLiberationfontquiverforeachfsfuturefuture.applygdtoolsgenericsGetoptLongggfunggiraphggplot2ggplotifyggrepelggridgesggtreeGlobalOptionsglobalsgluegoftestgplotsgridExtragridGraphicsgtablegtoolsherehighrhmshtmltoolshtmlwidgetshttpuvhttrhttr2icaigraphIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglaterlatticelazyevallifecyclelistenvlmtestmagrittrMASSMatrixmatrixStatsmemoisemimeminiUInlmeopensslotelpaletteerparallellypatchworkpbapplyphangornpillarpkgconfigplotlyplyrpngpolyclipprettyunitsprismaticprogressprogressrpromisesproxypurrrquadprogR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLrematch2reshape2reticulaterjsonrlangrmarkdownROCRrprojrootRSpectraRSQLiterstudioapiRtsneS4VectorsS7sassscalesscattermoresctransformSeqinfoSeuratSeuratObjectshapeshinysitmosourcetoolsspspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsyssystemfontstensortibbletidyrtidyselecttidytreetinytextreeioutf8uwotvctrsviridisLitewithrxfunxml2xtableXVectoryamlyulab.utilszoo

Advanced Visualization
Overview | CNV Heatmaps | Example CNV Heatmap | Basic Heatmap | Customizing Heatmaps | Split by Cell Type | Split by CNV Clusters | Custom Color Scheme | Heatmap Components | Phylogenetic Trees | Example Dendrogram | Building CNV Trees | Visualizing Trees | Annotated Trees | Tree Interpretation | Chromosome Arm-Level Analysis | Example: CNV Fraction per Chromosome Arm | Computing Arm-Level CNVs | Visualizing Arm-Level CNVs | Spatial CNV Visualization | Visium Data | Visium HD Data | Combining Spatial and CNV Information | Custom Visualizations | Extracting CNV Data | Creating Custom Plots | Comparing Clusters | Publication-Ready Figures | High-Resolution Export | Figure Panel Assembly | Color Palettes | Default Palettes | Custom Palettes | Tips and Best Practices | 1. Heatmap Ordering | 2. Color Scaling | 3. Resolution Selection | 4. Figure Legends | Session Info
Rendered fromvisualization.Rmdusingknitr::rmarkdown

Last update: 2026-01-23
Started: 2026-01-23

Algorithm and Methodology
Theoretical Background | Copy Number Variations in Cancer | Expression-Based CNV Inference | Algorithm Pipeline | Step 1: Gene Ordering | Step 2: Sliding Window Smoothing | Step 3: Reference Normalization | Step 4: Score Computation | Step 5: Quantile-Based Thresholding | Step 6: Hierarchical Clustering | Mathematical Details | Distance Metric | CNV Classification | Performance Optimization | Vectorized Operations | Memory Management | Algorithm Parameters Summary | Validation and Quality Control | Checking Results | References | Session Info
Rendered fromalgorithm.Rmdusingknitr::rmarkdown

Last update: 2026-01-23
Started: 2026-01-23

Introduction to fastCNV
Overview | Example Output: CNV Heatmap | Key Features | Installation | From R-universe (Recommended) | From GitHub | Quick Start | Basic Workflow | Understanding the Parameters | Examining Results | Example Output: Single Cell CNV Profile | Supported Data Types | Single-Cell RNA-seq | 10X Visium | 10X Visium HD | Next Steps | Session Info | Citation | Contact
Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2026-01-23
Started: 2026-01-23

Multi-Sample Analysis
Overview | Preparing Multiple Samples | Loading Samples | Sample List Preparation | Running Multi-Sample Analysis | Basic Multi-Sample Workflow | Pooled Reference Analysis | Handling Results | Accessing Individual Results | Merging Results | Cross-Sample Comparisons | Comparing CNV Patterns | Chromosome Arm Comparison | Identifying Recurrent CNVs | Finding Common Events | Visualizing Recurrent CNVs | Batch Effect Considerations | Detecting Batch Effects | Mitigating Batch Effects | Cohort-Level Visualization | Combined Heatmap | Sample-Wise CNV Tree | Memory Management | Large Cohort Processing | Parallel Processing | Case Study: Tumor Cohort Analysis | Workflow Example | Summary | Session Info
Rendered frommulti-sample.Rmdusingknitr::rmarkdown

Last update: 2026-01-23
Started: 2026-01-23

Readme and manuals

Help Manual

Help pageTopics
Annotate a Phylogenetic Tree with CNV EventsannotateCNVTree
Project 8µm Spatial Annotation onto 16µm Spotsannotations8umTo16um
Construct a Phylogenetic Tree from a Copy Number Variation (CNV) MatrixbuildCNVTree
CNVAnalysis Runs Copy Number Variation (CNV) analysis on a Seurat object or a list of Seurat objects.CNVAnalysis
CNVCalling Performs Copy Number Variation (CNV) analysis on a Seurat object.CNVCalling
CNVCalling for a List of Seurat Objects Performs Copy Number Variation (CNV) analysis on a list of Seurat objects.CNVCallingList
CNV Classification Classifies the CNV results into loss, gain, or no alteration for each observation and chromosome arm.CNVClassification
Perform CNV Clustering with Seurat ObjectCNVCluster
CNV Per Chromosome Arm Computes the CNV fraction of each spot/cell per chromosome arm, then stores the results into the metadata.CNVPerChromosomeArm
Build, annotate and plot a Phylogenetic Tree from a seurat Object containing the CNV results from 'fastCNV()'CNVTree
Compute average expression for patientscomputeAverageExpression
Fast CNV Detection for Single-Cell and Spatial Transcriptomics DatafastCNV
fastCNV_10XHD calls all of the internal functions needed to compute the putative CNV on a Seurat Visium HD object or a list of Seurat Visium HD objectsfastCNV_10XHD
Genes Data from Ensembl Version 113geneMetadata
Generate CNV Matrix for CNV Clusters by Chromosome ArmgenerateCNVClonesMatrix
Download Gene Information from EnsemblgetGenes
Merge CNV Clusters in a Seurat ObjectmergeCNVClusters
Plot CNV Results into a Heatmap Builds a heatmap to visualize the CNV results based on genomic scores.plotCNVResults
Plot Visium HD CNV Results into a Heatmap Builds a heatmap to visualize the Visium HD CNV results based on genomic scores.plotCNVResultsHD
Plot an Annotated Phylogenetic Tree with CNV EventsplotCNVTree
Aggregate Observations by Cell Type for CNV Analysis Aggregates observations with the same cell types to increase counts per observation, improving Copy Number Variation (CNV) computation.prepareCountsForCNVAnalysis