This is the development version of spacexr; for the stable release version, see spacexr.
SpatialeXpressionR: Cell Type Identification in Spatial TranscriptomicsBioconductor version: Development (3.22)
Spatial-eXpression-R (spacexr) is a package for analyzing cell types in spatial transcriptomics data. This implementation is a fork of the spacexr GitHub repo (https://github.com/dmcable/spacexr), adapted to work with Bioconductor objects. The original package implements two statistical methods: RCTD for learning cell types and CSIDE for inferring cell type-specific differential expression. Currently, this fork only implements RCTD, which learns cell type profiles from annotated RNA sequencing (RNA-seq) reference data and uses these profiles to identify cell types in spatial transcriptomic pixels while accounting for platform-specific effects. Future releases will include an implementation of CSIDE.
Author: Dylan Cable [aut], Gabriel Grajeda [cre] ORCID: 0009-0003-7242-7476 , Fannie and John Hertz Foundation [fnd]
Maintainer: Gabriel Grajeda <gabriel.grajeda at gmail.com>
Citation (from within R, entercitation("spacexr")): 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("spacexr")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("spacexr")Follow Installation instructions to use this package in your R session.
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