E. Spatial, Multi-Modal and Extended Analysis

Directions

This article serves as pointer to additional resources for spatial and other data types in the Bioconductor and Seurat communities.

Bioconductor

In Bioconductor a good starting resource is Orchestrating Spatially-Resolved Transcriptomics Analysis with Bioconductor. Check out biocViews (e.g., the spatial term) and new packages in the most recent release. A key feature of Bioconductor packages is the vignette, so be sure to review vignettes of any package that seems interesting. Follow guidelines (it’s not as intimidating as it seems!) to contribute your own methods.

Seurat

The Seurat community has links from the Getting Started page to resources for multi-modal and spatial transcriptomic analysis. Seurat provides a wrappers for enabling (re)-distribution packages in a way that encourages use in the Seurat community.

Python

scanpy and anndata represent key Python resources. For R users wishing to integrate Python steps into an overall analysis a reasonable strategy is to use the reticulate package to invoke Python from R; the anndata R package provides a convenient wrapper around anndata in Python and we used this in the training_read_h5ad_as_*() functions.