Our online textbook Orchestrating Spatially Resolved Transcriptomics Analysis with Bioconductor (OSTA) describes the steps in a computational analysis pipeline for spatially resolved transcriptomics (ST) data using the Bioconductor framework in R, including examples and workflows with R code and datasets.
OSTA is built around the SpatialExperiment object class and the Bioconductor principle of modularity, which allows users to easily adapt the pipeline to substitute alternative or updated methods for individual steps.
In particular, OSTA and
SpatialExperiment are compatible with SingleCellExperiment, allowing existing methods and pipelines developed for single-cell RNA sequencing data (such as those described in OSCA) to be re-used and adapted to the spatial context.
For this workshop, we will use R version 4.1 and a
devel installation of Bioconductor 3.14. In addition, you will need to install the following package from GitHub:
remotes::install_github("lmweber/ggspavis", build_vignettes = TRUE)
Alternatively, you can use a
release version of Bioconductor 3.13 along with the following versions of packages installed from GitHub:
remotes::install_github("drighelli/SpatialExperiment", build_vignettes = TRUE) remotes::install_github("lmweber/STexampleData", ref = "no_accessors", build_vignettes = TRUE) remotes::install_github("lmweber/ggspavis", build_vignettes = TRUE)
A Docker image containing a complete version of all materials used in the workshop is also available. Note this is a large download.
To run the Docker image:
docker run -e PASSWORD=abc -p 8787:8787 lmweber/ostaworkshopbioc2021:latest
Then navigate to http://localhost:8787/ in your browser, and log in with username
rstudio and password