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DESpace

This is the development version of DESpace; for the stable release version, see DESpace.

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


Bioconductor version: Development (3.21)

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.

Author: Peiying Cai [aut, cre] (ORCID: ), Simone Tiberi [aut] (ORCID: )

Maintainer: Peiying Cai <peiying.cai at uzh.ch>

Citation (from within R, enter citation("DESpace")):

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")
A framework to discover spatially variable genes HTML R Script
Differential Spatial Pattern between conditions HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Spatial, StatisticalMethod, Transcriptomics, Visualization
Version 1.99.1
In Bioconductor since BioC 3.17 (R-4.3) (2 years)
License GPL-3
Depends R (>= 4.5.0)
Imports edgeR, limma, dplyr, stats, Matrix, SpatialExperiment, ggplot2, ggpubr, SummarizedExperiment, S4Vectors, BiocGenerics, data.table, assertthat, sosta, cowplot, ggforce, ggnewscale, patchwork, BiocParallel, methods, muscat, scales
System Requirements
URL https://github.com/peicai/DESpace
Bug Reports https://github.com/peicai/DESpace/issues
See More
Suggests knitr, rmarkdown, testthat, BiocStyle, ExperimentHub, spatialLIBD, purrr, scuttle, utils, reshape2, tidyverse, concaveman
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package DESpace_1.99.1.tar.gz
Windows Binary (x86_64) DESpace_1.99.1.zip (64-bit only)
macOS Binary (x86_64) DESpace_1.99.1.tgz
macOS Binary (arm64) DESpace_1.99.1.tgz
Source Repository git clone https://git.bioconductor.org/packages/DESpace
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/DESpace
Bioc Package Browser https://code.bioconductor.org/browse/DESpace/
Package Short Url https://bioconductor.org/packages/DESpace/
Package Downloads Report Download Stats