Package: spacexr 1.4.0

spacexr: SpatialeXpressionR: Cell Type Identification in Spatial Transcriptomics

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.

Authors:Dylan Cable [aut], Rafael Irizarry [aut], Gabriel Grajeda [cre], Fannie and John Hertz Foundation [fnd]