Package: SpaceMarkers 2.2.0

Atul Deshpande

SpaceMarkers: Spatial Interaction Markers

Spatial transcriptomic technologies have helped to resolve the connection between gene expression and the 2D orientation of tissues relative to each other. However, the limited single-cell resolution makes it difficult to highlight the most important molecular interactions in these tissues. SpaceMarkers, R/Bioconductor software, can help to find molecular interactions, by identifying genes associated with latent space interactions in spatial transcriptomics.

Authors:Atul Deshpande [aut, cre], Ludmila Danilova [ctb], Dmitrijs Lvovs [ctb]

SpaceMarkers_2.2.0.tar.gz
SpaceMarkers_2.2.0.zip(r-4.7)SpaceMarkers_2.2.0.zip(r-4.6)SpaceMarkers_2.2.0.zip(r-4.5)
SpaceMarkers_2.2.0.tgz(r-4.6-any)SpaceMarkers_2.2.0.tgz(r-4.5-any)
SpaceMarkers_2.2.0.tar.gz(r-4.7-any)SpaceMarkers_2.2.0.tar.gz(r-4.6-any)
SpaceMarkers_2.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SpaceMarkers/json (API)
NEWS

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

Bug tracker:https://github.com/deshpandelab/spacemarkers/issues

Datasets:

On BioConductor:SpaceMarkers-2.3.1(bioc 3.24)SpaceMarkers-2.2.0(bioc 3.23)

singlecellgeneexpressionsoftwarespatialtranscriptomics

6.38 score 8 stars 30 scripts 252 downloads 25 exports 140 dependencies

Last updated from:e099a7dc97 (on RELEASE_3_23). Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksERROR228
linux-devel-x86_64NOTE414
source / vignettesOK592
linux-release-x86_64NOTE426
macos-release-arm64NOTE461
macos-oldrel-arm64NOTE232
windows-develNOTE315
windows-releaseNOTE309
windows-oldrelNOTE342
wasm-releaseOK200

Exports:calculate_gene_scores_directedcalculate_gene_set_scorecalculate_gene_set_specificitycalculate_influencecalculate_lr_scorescalculate_overlap_directedcalculate_overlap_undirectedcalculate_thresholdsfind_all_hotspotsfind_hotspots_gmmfind_pattern_hotspotsget_im_scoresget_interacting_genesget_pairwise_interacting_genesget_spatial_featuresget_spatial_parametersget_spatial_params_morans_iload10XCoordsload10XExprplot_cell_interaction_circosplot_im_scoresplot_overlap_scoresplot_source_to_target_circosplot_spatial_data_over_imageplot_target_from_sources_circos

Dependencies:abindapeaskpassbackportsbase64encbitbit64bmpbootbroombslibcachemcarcarDatacirclizeclicolorspacecorrplotcowplotcpp11crosstalkcurldata.tabledeldirDerivdigestdoBydplyreffsizeevaluatefarverfastmapfontawesomeforecastFormulafracdifffsgenericsggplot2GlobalOptionsgluegoftestgridExtragtablehdf5rhighrhtmltoolshtmlwidgetshttrisobandjpegjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevallifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmatrixStatsmatrixTestsmemoisemgcvmicrobenchmarkmimeminqamixtoolsmodelrnanoparquetnlmenloptrnnetnumDerivopensslotelpbkrtestpillarpkgconfigplotlyplyrpngpolyclippromisespurrrquantregqvalueR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadbitmapreformulasreshape2rlangrmarkdownrstatixS7sassscalessegmentedshapeSparseMspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsystensortibbletidyrtidyselecttifftimeDatetinytexurcautf8vctrsviridisviridisLitewithrxfunyamlzoo

Inferring Immune Interactions in Breast Cancer

Orian Stapleton

Rendered fromSpaceMarkers_vignette.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2025-10-24
Started: 2024-07-16

Readme and manuals

Help Manual

Help pageTopics
Calculate interaction scores for a specific pattern pair.calc_IM_scores
Compute the threshold for identifying outlier values or hotspots.calc_threshold
.find_genes_of_interest Identify genes associated with pattern interaction. This function identifies genes exhibiting significantly higher values of testMat in the Interaction region of the two patterns compared to regions with exclusive influence from either pattern. It uses Kruskal-Wallis test followed by posthoc analysis using Dunn's Test to identify the genes..find_genes_of_interest
.pick_image.pick_image
Perform row-wise t-tests from scratch.row_t_test
Calculate interaction scores for all pattern pairscalculate_gene_scores_directed
calculate_gene_set_scorecalculate_gene_set_score
calculate_gene_set_specificitycalculate_gene_set_specificity
Compute the spatial influence of a spatial featurecalculate_influence
calculate_lr_scorescalculate_lr_scores
calculate_overlap_directedcalculate_overlap_directed
calculate_overlap_undirectedcalculate_overlap_undirected
Compute the thresholds for all columns in a data framecalculate_thresholds
Curated Genes for example purposescurated_genes
Find hotSpots for all spatial patternsfind_all_hotspots
Find hotspots for all patterns or influences based on valuesfind_hotspots_gmm
Identify hotspots of spatial pattern influencefind_pattern_hotspots
get_im_scoresget_im_scores
Calculate Interaction Regions and Associated Genesget_interacting_genes
get_pairwise_interacting_genesget_pairwise_interacting_genes
Load spatial featuresget_spatial_features
Read optimal parameters for spatial kernel density from user input or .json fileget_spatial_parameters
Calculate the optimal parameters from spatial kernel density for cell-cell interactionsget_spatial_params_morans_i
Load 10x Visium Spatial Coordinatesload10XCoords
Load 10X Visium Expression Dataload10XExpr
Curated Ligand-receptor interaction genes A list of vectors with genes associated with ligand-receptor interactions from CellChat databaselrdf
Optimal paramters of 5 patterns from CoGAPS.optParams
Plot Ligand-Receptor Interactions between Cell Typesplot_cell_interaction_circos
plot_im_scoresplot_im_scores
plot_overlap_scoresplot_overlap_scores
Plot Ligand-Receptor Interactions from a Single Source to Target Cell Typesplot_source_to_target_circos
plotSpatialDataOverImageplot_spatial_data_over_image
Plot Ligand-Receptor Interactions from Multiple Source to a Single Target Cell Typeplot_target_from_sources_circos