BayesSpace

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 3.12+. Specific package dependencies
are defined in the package DESCRIPTION and are managed by the Bioconductor and
devtools installers.

Installation

BayesSpace is available through
Bioconductor.

# Install the Bioconductor package manager, if necessary
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("BayesSpace")

The development version can be installed via Bioconductor (see instructions on
using the devel
branch) or from
github 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.

Download links for the appropriate macOS versions can be found here:

• Mojave (10.14) and Catalina (10.15) - gfortran8.2
• Sierra (10.12) and High Sierra (10.13) - gfortran6.3

Additional details on installing the R compiler tools for Rcpp on macOS can be
found in this blog
post.

Note about homebrew: While gfortran is available via homebrew, we’ve
encountered issues linking to its libraries after installation. We recommend
installing directly from the GNU Fortran
repo.

Demonstration

For an example of typical BayesSpace usage, please see our package
vignette
for a demonstration and overview of the functions included in BayesSpace.

Running the entire vignette takes approximately 5m30s on a Macbook Pro with a
2.0 GHz quad-core processor and 16 GB of RAM.