DESpace
This is the released version of DESpace; for the devel version, see DESpace.
DESpace: a framework to discover spatially variable genes and differential spatial patterns across conditions
Bioconductor version: Release (3.23)
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. See Cai et al. (2024) <doi:10.1093/bioinformatics/btae027> and Cai et al. (2026) <doi:10.1093/bioinformatics/btag450>.
Author: Peiying Cai [aut, cre] 
, Mark D. Robinson [aut] , Simone Tiberi [aut]
Maintainer: Peiying Cai <peiying.cai at uzh.ch>
citation("DESpace")):Peiying Cai, Mark D. Robinson, Simone Tiberi. DESpace: DESpace: a framework to discover spatially variable genes and differential spatial patterns across conditions. doi:10.18129/B9.bioc.DESpace, R package version 2.4.1, https://bioconductor.org/packages/DESpace.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("DESpace")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DESpace")| Differential Spatial Pattern between conditions | HTML | R Script |
| A framework to discover spatially variable genes | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DifferentialExpression, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Spatial, StatisticalMethod, Transcriptomics, Visualization |
| Version | 2.4.1 |
| In Bioconductor since | BioC 3.17 (R-4.3) (3.5 years) |
| License | GPL-3 |
| Depends | R (>= 4.5.0) |
| Imports | edgeR, limma, dplyr, stats, Matrix, SpatialExperiment, ggplot2, SummarizedExperiment, S4Vectors, BiocGenerics, data.table, assertthat, terra, sf, spatstat.explore, spatstat.geom, ggforce, ggnewscale, patchwork, BiocParallel, methods, scales, scuttle |
| System Requirements | |
| URL | https://github.com/peicai/DESpace https://peicai.github.io/DESpace/ |
| Bug Reports | https://github.com/peicai/DESpace/issues |
See More
| Suggests | knitr, rmarkdown, testthat, BiocStyle, muSpaData, ExperimentHub, spatialLIBD, purrr, reshape2, tidyverse, concaveman |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | OSTA |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | DESpace_2.4.1.tar.gz |
| Windows Binary (x86_64) | DESpace_2.4.1.zip (64-bit only) |
| macOS Binary (big-sur-x86_64) | DESpace_2.4.1.tgz |
| macOS Binary (sonoma-arm64) | DESpace_2.4.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/DESpace |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/DESpace |
| Package Short Url | https://bioconductor.org/packages/DESpace/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.23 | Source Archive |