DESpace

DOI: 10.18129/B9.bioc.DESpace  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see DESpace.

DESpace: a framework to discover spatially variable genes

Bioconductor version: 3.17

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, cte]

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

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")

 

HTML	R Script	A framework to discover spatially variable genes
PDF		Reference Manual
Text		NEWS

Details

biocViews	DifferentialExpression, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Spatial, StatisticalMethod, Transcriptomics, Visualization
Version	1.0.0
In Bioconductor since	BioC 3.17 (R-4.3) (< 6 months)
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
LinkingTo
Suggests	knitr, rmarkdown, testthat, BiocStyle, ExperimentHub, concaveman, spatialLIBD, purrr, scuttle, utils
SystemRequirements
Enhances
URL	https://github.com/peicai/DESpace
BugReports	https://github.com/peicai/DESpace/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	DESpace_1.0.0.tar.gz
Windows Binary	DESpace_1.0.0.zip
macOS Binary (x86_64)	DESpace_1.0.0.tgz
macOS Binary (arm64)	DESpace_1.0.0.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