Awesome

Welcome to `SPOTlight` <img src="inst/extdata/SPOTlight.png" width="200" align="right"/>

Current build status

release
development

We are currently on the process of submitting SPOTlight to bioconductor and there have been some styling changes on this branch compared to previous releases. If you want to use the version we are currently submitting feel free to look at the updated vignette here. If you want to keep using the previous versions, you can still find it in the spotlight-0.1.7 branch and follow the previous vignette.

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 dense and sparse matrices. 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?