Package: SpaTalk 2.0.0

SpaTalk: Spatially Resolved Cell-Cell Communication Inference for Spatial Transcriptomics

Infers spatially resolved cell-cell communications from spatial transcriptomics data using graph network and knowledge graph approaches. Supports both single-cell resolution and spot-based spatial transcriptomics platforms. Provides cell type deconvolution, ligand-receptor interaction analysis, and downstream pathway inference.

Authors:Zaoqu Liu [aut, cre], Xin Shao [aut]

SpaTalk_2.0.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SpaTalk/json (API)

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

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

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

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.99 score 39 scripts 41 exports 207 dependencies

Last updated from:a892134716 (on main). Checks:10 WARNING, 2 OK, 3 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING284
linux-devel-x86_64WARNING352
source / vignettesOK503
linux-release-arm64WARNING325
linux-release-x86_64WARNING340
macos-release-arm64WARNING202
macos-release-x86_64WARNING457
macos-oldrel-arm64FAIL136
macos-oldrel-x86_64FAIL340
windows-devel-arm64WARNING414
windows-devel-x86_64WARNING364
windows-release-arm64WARNING409
windows-release-x86_64WARNING319
windows-oldrel-x86_64FAIL112
wasm-releaseOK220

Exports:cpp_batch_coexpcpp_batch_corcpp_coexp_fastcpp_fast_distcpp_fast_samplingcpp_knncpp_permutation_testcpp_random_walkcreateSpaTalkdec_ccidec_cci_alldec_celltypedemo_dec_resultdemo_geneinfodemo_lrpairsdemo_pathwaysdemo_sc_datademo_st_datademo_st_metademo_st_sc_datademo_st_sc_metafind_lr_pathgenerate_spotget_lr_pathplot_ccdistplot_cci_lrpairsplot_lr_pathplot_lrpairplot_lrpair_vlnplot_path2geneplot_st_celltypeplot_st_celltype_allplot_st_celltype_densityplot_st_celltype_percentplot_st_cor_heatmapplot_st_geneplot_st_pieplot_st_pie_generaterev_geneset_expected_cellshow

Dependencies:abindaskpassbackportsbase64encBHbitbit64bitopsbootbroombslibcachemcarcarDatacaToolscirclizeclicliprclustercodetoolscolorspacecolourpickercommonmarkcorrplotcowplotcpp11crayoncrosstalkcurldata.tabledeldirDerivdigestdoBydoParalleldotCall64dplyrdqrngevaluatefarverfastDummiesfastmapfitdistrplusFNNfontawesomeforeachforecastFormulafracdifffsfuturefuture.applygenericsggalluvialggExtraggforceggfunggplot2ggpubrggraphggrepelggridgesggsciggsignifGlobalOptionsglobalsgluegoftestgplotsgraphlayoutsgridExtragtablegtoolsherehighrhmshtmltoolshtmlwidgetshttpuvhttricaigraphirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelistenvlme4lmtestmagrittrMASSMatrixMatrixModelsmatrixStatsmemoisemgcvmimeminiUIminqamodelrnlmenloptrnnetnumDerivopensslotelparallellypatchworkpbapplypbkrtestpheatmappillarpkgconfigplotlyplyrpngpolyclippolynomprettyunitsprogressprogressrpromisespurrrquantregR6RANNrappdirsrbibutilsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppThreadRcppTOMLRdpackreadrreformulasreshape2reticulaterlangrmarkdownROCRrprojrootRSpectrarstatixRtsneS7sassscalesscattermorescatterpiesctransformSeuratSeuratObjectshapeshinyshinyjssitmosourcetoolsspspamSparseMspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsyssystemfontstensortibbletidygraphtidyrtidyselecttimeDatetinytextweenrtzdburcautf8uwotvctrsviridisviridisLitevroomwithrxfunxtableyamlyulab.utilszoo

SpaTalk for Different Spatial Transcriptomics Platforms
Overview | Single-Cell Resolution Platforms | STARmap Example (Built-in Data) | Other Single-Cell Platforms | Spot-Based Platforms | 10x Visium Workflow | Slide-seq / Slide-seqV2 | Workflow Comparison | Single-cell Workflow (STARmap, MERFISH, Xenium) | Spot-based Workflow (Visium, Slide-seq) | Parameter Guidelines by Platform | Best Practices | For Spot-based Data | For Single-cell Data | Session Info
Rendered fromplatforms.Rmdusingknitr::rmarkdown

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

SpaTalk Visualization Guide
Introduction | Setup | Spatial Cell Type Visualization | plot_st_celltype_all | plot_st_celltype | plot_st_celltype_density | Gene Expression Visualization | plot_st_gene | Advanced Visualizations (After CCI Analysis) | plot_ccdist | plot_lrpair | Customization Tips | Custom Themes | Summary of Visualization Functions | Session Info
Rendered fromvisualization.Rmdusingknitr::rmarkdown

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

SpaTalk: Quick Start Guide
Introduction | Citation | Key Features | Installation | Quick Start with STARmap Data | Step 1: Load Package and Data | Step 2: Create SpaTalk Object | Step 3: Visualize Spatial Distribution | Step 4: Filter LR-Pathway Pairs | Step 5: Infer Cell-Cell Communications | Step 6: Visualize Results | Cell-Cell Distance Distribution | LR Pair Spatial Distribution | Next Steps | Session Info
Rendered fromSpaTalk.Rmdusingknitr::rmarkdown

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

SpaTalk Advanced Usage
Introduction | Custom Databases | Custom Ligand-Receptor Pairs | Custom Pathway Database | Alternative Deconvolution Methods | Method 1: Built-in NNLM (Default) | Method 2: RCTD (spacexr) | Method 3: Seurat Integration | Method 4: SPOTlight | Method 5: deconvSeq | Method 6: stereoscope (Python) | Method 7: cell2location (Python) | Parallel Processing | Enabling Parallel Processing | Memory Optimization | Platform-Specific Workflows | 10x Visium | Slide-seq | STARmap / MERFISH (Single-cell resolution) | Extracting Results | LR Pair Results | Downstream TF Scores | Full CCI Network | Troubleshooting | Common Issues | Best Practices | Session Info
Rendered fromadvanced.Rmdusingknitr::rmarkdown

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

SpaTalk Algorithm: Methodological Framework
Overview | Algorithmic Pipeline | 1. Cell-Type Deconvolution | Mathematical Formulation | NNLM Algorithm | 2. Spatial Reconstruction | Monte Carlo Spatial Sampling | k-Nearest Neighbor Mapping | 3. Knowledge Graph Integration | LR-Pathway Database | Pathway Filtering Algorithm | 4. Cell-Cell Communication Inference | Co-expression Score | Permutation Test | 5. Downstream Pathway Scoring | Random Walk Algorithm | C++ Implementation | Computational Complexity | References | Session Info
Rendered fromalgorithm.Rmdusingknitr::rmarkdown

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

Readme and manuals

Help Manual

Help pageTopics
Use Rcpp for fast permutation if available.use_cpp_permutation
Use Rcpp for fast random walk if available.use_cpp_random_walk
Calculate co-expression for multiple gene pairscpp_batch_coexp
Calculate correlation between a vector and matrix columnscpp_batch_cor
Calculate co-expression ratioscpp_coexp_fast
Calculate Euclidean distance matrixcpp_fast_dist
Sample cells to reconstruct spot expressioncpp_fast_sampling
Find K nearest neighborscpp_knn
Permutation test for LR co-expression significancecpp_permutation_test
Random walk on gene-gene interaction networkcpp_random_walk
SpaTalk objectcreateSpaTalk
Decomposing cell-cell communications for spatial transciptomics datadec_cci
Decomposing cell-cell communications for spatial transciptomics datadec_cci_all
Decomposing cell type for spatial transcriptomics datadec_celltype
Demo data of dec_resultdemo_dec_result
Demo data of geneinfodemo_geneinfo
Demo data of lrpairsdemo_lrpairs
Demo data of pathwaysdemo_pathways
Demo data of sc_datademo_sc_data
Demo data of st_datademo_st_data
Demo data of st_metademo_st_meta
Demo data of single-cell st_datademo_st_sc_data
Demo data of st_sc_metademo_st_sc_meta
Find lrpairs and pathwaysfind_lr_path
geneinfogeneinfo
Generate pseudo spot st_datagenerate_spot
Get LR and downstream pathwaysget_lr_path
lrpairslrpairs
pathwayspathways
Plot cell-cell distributionplot_ccdist
Plot LR pairsplot_cci_lrpairs
Plot LR and downstream pathwaysplot_lr_path
Plot LR pairplot_lrpair
Plot spatial distance of LR pair with vlnplotplot_lrpair_vln
River plot of significantly activated pathways and related downstream genes of receptors.plot_path2gene
Plot spatial distribution of a single cell typeplot_st_celltype
Plot spatial distribution of all cell typesplot_st_celltype_all
Plot spatial density of a single cell typeplot_st_celltype_density
Plot spatial distribution of a single cell type percentplot_st_celltype_percent
Plot heatpmap of correlation between marker genes and cell typesplot_st_cor_heatmap
Plot spatial distribution of geneplot_st_gene
Plot spatial transcriptomics dataplot_st_pie
Plot spatial transcriptomics dataplot_st_pie_generate
Pre-processing step: revising gene symbolsrev_gene
Set the expected cellset_expected_cell
Show SpaTalk objectshow,SpaTalk-method
Definition of 'SpaTalk' classSpaTalk SpaTalk-class