SPOTlight provides a tool that enables the deconvolution of mixtures of cells from a single-cell reference. Originally developed for 10X’s Visium - spatial transcriptomics- technology, it can be used for all technologies that output mixtures of cells. It is compatible with Bioconductor’s SingleCellExperiment and SpatialExperiment classes as well as with Seurat objects. Furthermore, the package also provides visualization tools to assess the results of the deconvolution. Briefly, SPOTlight is based on finding topic profile signatures, by means of an NMFreg model, for each cell type and then optimizing the cell types proportions to fit the mixture we want to deconvolute.
Installation
install.packages("BiocManager")
BiocManager::install("SPOTlight")
# Or the devel version
BiocManager::install("SPOTlight", version = "devel")Alternatively, you can install it from GitHub using the devtools package.
install.packages("devtools")
library(devtools)
install_github("https://github.com/MarcElosua/SPOTlight")References
- Elosua-Bayes M, Nieto P, Mereu E, Gut I, Heyn H (2021): SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes. Nucleic Acids Res 49(9):e50. doi:10.1093/nar/gkab043.
Contributors
SPOTlight was originally developed by Marc Elosua Bayes and has received substantial additional contributions from Helena L. Crowell.
Issues - Ideas?
SPOTlight is still under active development. We greatly welcome (and highly encourage!) all feedback, bug reports and suggestions for improvement here. Please make sure to raise issues with a reproducible example and the output of your sessionInfo().