Package: DESpace 2.5.0

Peiying Cai

DESpace: DESpace: a framework to discover spatially variable genes and differential spatial patterns across conditions

Intuitive framework for identifying spatially variable genes (SVGs) and differential spatial variable pattern (DSP) between conditions via edgeR, a popular method for performing differential expression analyses. Based on pre-annotated spatial clusters as summarized spatial information, DESpace models gene expression using a negative binomial (NB), via edgeR, with spatial clusters as covariates. SVGs are then identified by testing the significance of spatial clusters. For multi-sample, multi-condition datasets, we again fit a NB model via edgeR, incorporating spatial clusters, conditions and their interactions as covariates. DSP genes-representing differences in spatial gene expression patterns across experimental conditions-are identified by testing the interaction between spatial clusters and conditions.

Authors:Peiying Cai [aut, cre], Simone Tiberi [aut]

DESpace_2.5.0.tar.gz
DESpace_2.5.0.zip(r-4.7)DESpace_2.5.0.zip(r-4.6)DESpace_2.5.0.zip(r-4.5)
DESpace_2.5.0.tgz(r-4.6-any)DESpace_2.5.0.tgz(r-4.5-any)
DESpace_2.5.0.tar.gz(r-4.7-any)DESpace_2.5.0.tar.gz(r-4.6-any)
DESpace_2.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DESpace/json (API)
NEWS

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

Bug tracker:https://github.com/peicai/despace/issues

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

Datasets:

On BioConductor:DESpace-2.5.0(bioc 3.24)DESpace-2.4.0(bioc 3.23)

spatialsinglecellrnaseqtranscriptomicsgeneexpressionsequencingdifferentialexpressionstatisticalmethodvisualization

6.34 score 7 stars 52 scripts 439 downloads 6 exports 114 dependencies

Last updated from:b5a1ab3929. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE299
linux-devel-x86_64OK531
source / vignettesOK852
linux-release-x86_64OK573
macos-release-arm64OK336
macos-oldrel-arm64OK285
windows-develOK1174
windows-releaseOK1178
windows-oldrelOK1170
wasm-releaseOK270

Exports:dsp_testFeaturePlotindividual_dspindividual_svgsvg_testtop_results

Dependencies:abindaskpassassertthatassortheadbase64encbeachmatBHBiobaseBiocFileCacheBiocGenericsBiocParallelbitbit64blobcachemclassclassIntclicodetoolscpp11curldata.tableDBIdbplyrDelayedArraydeldirdplyre1071edgeRfarverfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomicRangesggforceggnewscaleggplot2gluegoftestgtablehttr2IRangesisobandjsonliteKernSmoothlabelinglambda.rlatticelifecyclelimmalocfitmagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisenlmeopensslpatchworkpillarpkgconfigpolyclipproxypurrrR6rappdirsRColorBrewerRcpprjsonrlangRSQLites2S4ArraysS4VectorsS7scalesscuttleSeqinfosfSingleCellExperimentsnowSparseArraySpatialExperimentspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstatmodstringistringrSummarizedExperimentsyssystemfontstensorterratibbletidyrtidyselecttweenrunitsutf8vctrsviridisLitewithrwkXVector

A framework to discover Spatially Variable genes via spatial clusters

Peiying Cai, Simone Tiberi

Rendered fromSVG.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-03-28
Started: 2025-03-19

Differential Spatial Pattern between conditions

Peiying Cai, Simone Tiberi

Rendered fromDSP.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-11-28
Started: 2025-03-19