## Overview

BayesSpace provides tools for clustering and enhancing the resolution of spatial gene expression experiments.

BayesSpace clusters a low-dimensional representation of the gene expression matrix, incorporating a spatial prior to encourage neighboring spots to cluster together. The method can enhance the resolution of the low-dimensional representation into “sub-spots”, for which features such as gene expression or cell type composition can be imputed.

## System requirements

### Operating system

BayesSpace has been built and tested on the following operating systems:

• Linux: Ubuntu 18.04.4 LTS (Bionic Beaver)
• macOS: 10.14.6 (Mojave), 10.15.6 (Catalina)
• Windows: 10, Server 2012 R2 Standard

### Software dependencies

BayesSpace requires R 4.0 and Bioconductor 3.11. Specific package dependencies are defined in the package DESCRIPTION and are managed by the Bioconductor and devtools installers.

## Installation

BayesSpace has been submitted to Bioconductor. Until its availability there, it can be installed with devtools:

# Install devtools if necessary
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")

devtools::install_github("edward130603/BayesSpace")

Installation, including compilation, should take no more than one minute.

### Installing from source on macOS

Installing from source on macOS (such as when installing via devtools::install_github()) requires Fortran to compile the Rcpp code.