DESpace
This is the development version of DESpace; for the stable release version, see DESpace.
DESpace: a framework to discover spatially variable genes
Bioconductor version: Development (3.20)
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("DESpace")
):
Installation
To install this package, start R (version "4.4") 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 |
Reference Manual | ||
NEWS | Text |
Details
biocViews | DifferentialExpression, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Spatial, StatisticalMethod, Transcriptomics, Visualization |
Version | 1.5.0 |
In Bioconductor since | BioC 3.17 (R-4.3) (1.5 years) |
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 |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | DESpace_1.5.0.tar.gz |
Windows Binary | DESpace_1.5.0.zip |
macOS Binary (x86_64) | DESpace_1.5.0.tgz |
macOS Binary (arm64) | DESpace_1.5.0.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 |