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✨
DESCRIPTION |NEWS
card.svg |card.png
DESpace/json (API)

# 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

6.39 score 7 stars 58 scripts 6 exports 114 dependencies

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

TargetResultTimeFilesSyslog
bioc-checksNOTE375
linux-devel-x86_64OK619
source / vignettesOK814
linux-release-x86_64OK645
macos-release-arm64OK288
macos-oldrel-arm64OK401
windows-develOK1436
windows-releaseOK1268
windows-oldrelOK1109
wasm-releaseOK303

Exports:dsp_testFeaturePlotindividual_dspindividual_svgsvg_testtop_results

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

Differential Spatial Pattern between conditions
Introduction | Load packages | Data | Input data | Quality control/filtering | Clustering | Manual annotation | Spatially resolved (multi-sample) clustering | Single sample clustering | DSP testing | Gene-level test | Individual cluster test | Visualization | Abundance trend | Spatial expression | Smooth splines to model time | Predicted trend | Session info | References
Rendered fromDSP.Rmdusingknitr::rmarkdown

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

A framework to discover Spatially Variable genes via spatial clusters
Introduction | Basics | Data | Input data | Quality control/filtering | Individual sample | Clustering | Manual annotation | Spatially resolved clustering | BayesSpace | StLearn | SV testing | Gene-level test | Individual cluster test | Multiple samples | Spatially resolved (multi-sample) clustering | Single sample clustering | Sample-specific covariates (e.g., batch effects) | Session info | References
Rendered fromSVG.Rmdusingknitr::rmarkdown

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