We have developed two R packages to facilitate data analysis on our platform: emconnect and SpatialMap. emconnect is responsible for managing communication between Workbench, the Portal, and ATLAS. SpatialMap is our package for organizing and analyzing spatial datasets. It is similar to many Bioconductor packages (e.g. Seurat, SingleCellExperiment) in its philosophy of data management. An outline of the way SpatialMap organizes data is shown on the homepage of the package’s public documentation website.
You will most likely use SpatialMap for the bulk of your day-to-day analysis, which calls emconnect functions under the hood to pull in data from the Portal. However, if you have built your own atlas with multiple studies on our platform, emconnect may be useful to pull overviews and metadata summaries from your atlas (you can try running list_studies() to get an idea of what’s possible with emconnect).
To have access to these packages within your compute environment on Code Ocean, you should select the starter image Enable Medicine Base Image. For more information on configuring your compute environment on code ocean see Configuring and starting a cloud workstation.
SpatialMapA great place to get started with R on workbench is to look through the vignettes for our SpatialMap package, which you can view on the SpatialMap documentation website. These vignettes contain a demonstration of a complete spatial biology analysis workflow, and advanced tutorials that will provide a strong foundation for your analysis on Workbench.
In addition to browsing the vignettes on the website, you can also open their source code on Workbench. This allows you to run them interactively on Workbench, and to utilize this source code as a starting off point for analyzing your own data.
Accessing Source Code on Code Ocean
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