Bioconductor version: Release (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>
Citation (from within R,
enter citation("DESpace")
):
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.
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 |
Reference Manual | ||
Text | NEWS |
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 |
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 |
Old Source Packages for BioC 3.17 | Source Archive |
Documentation »
Bioconductor
R / CRAN packages and documentation
Support »
Please read the posting guide. Post questions about Bioconductor to one of the following locations: