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DESpace

DESpace: a framework to discover spatially variable genes


Bioconductor version: Release (3.18)

Intuitive framework for identifying spatially variable genes (SVGs) 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. The method is flexible and robust, and is faster than the most SV methods. Furthermore, to the best of our knowledge, it is the only SV approach that allows: - performing a SV test on each individual spatial cluster, hence identifying the key regions of the tissue affected by spatial variability; - jointly fitting multiple samples, targeting genes with consistent spatial patterns across replicates.

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

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

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

Installation

To install this package, start R (version "4.3") 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")
A framework to discover spatially variable genes HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Spatial, StatisticalMethod, Transcriptomics, Visualization
Version 1.2.1
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends R (>= 4.3.0)
Imports edgeR, limma, dplyr, stats, Matrix, SpatialExperiment, ggplot2, ggpubr, scales, SummarizedExperiment, S4Vectors, BiocGenerics, data.table, assertthat, cowplot, ggforce, ggnewscale, patchwork, BiocParallel, methods
System Requirements
URL https://github.com/peicai/DESpace
Bug Reports https://github.com/peicai/DESpace/issues
See More
Suggests knitr, rmarkdown, testthat, BiocStyle, ExperimentHub, concaveman, spatialLIBD, purrr, scuttle, utils
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Package Archives

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

Source Package DESpace_1.2.1.tar.gz
Windows Binary DESpace_1.2.1.zip
macOS Binary (x86_64) DESpace_1.2.1.tgz
macOS Binary (arm64) DESpace_1.2.1.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
Old Source Packages for BioC 3.18 Source Archive