The goal of SPOTlight is to provide a tool that enables the deconvolution of cell types and cell type proportions present within each capture locations comprising mixtures of cells, originally developed for 10X’s Visium - spatial trancsiptomics- technology, it can be used for all technologies returning mixtures of cells. SPOTlight is based on finding topic profile signatures, by means of an NMFreg model, for each cell type and finding which combination fits best the spot we want to deconvolute.

You can install the latest stable version from the GitHub repository SPOTlight with:

# install.packages("devtools")
devtools::install_github("https://github.com/MarcElosua/SPOTlight")
devtools::install_git("https://github.com/MarcElosua/SPOTlight")

Or the latest version in development by downloading the devel branch

devtools::install_github("https://github.com/MarcElosua/SPOTlight", ref = "devel")
devtools::install_git("https://github.com/MarcElosua/SPOTlight", ref = "devel")

To ensure the environment is compatible we have put out a docker environment that can be downloaded from DockerHub.
To download the R environment image

# R environment
docker pull marcelosua/spotlight_env_r:latest

To download the R studio image

# Rstudio environment
docker pull marcelosua/spotlight_env_rstudio:latest

Run the following command in the terminal

docker run -e PASSWORD=pwd -p 8787:8787 marcelosua/spotlight_env_rstudio 

Go to http://localhost:8787/ or other port you’ve set before.

Log in with:

username: rstudio

password: pwd # Same password as set in the above command (pwd)

In the Rstudio environment you can upload files and carry out analysis there, to save the files from the RStudio server click on More (gear) and export the desired files.

For more information check out the rocker project guidelines https://hub.docker.com/r/rocker/rstudio/

A vignette on how to run the basic SPOTlight workflow can be found here