Analyzing Spatially-Resolved Transcriptomics Data from Visium using spatialLIBD

Analyzing Spatially-Resolved Transcriptomics Data from Visium using spatialLIBD

Author(s): Louise A. Huuki-Myers,Nicholas J Eagles,Leonardo Collado Torres

Affiliation(s): Lieber Institute for Brain Development

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Spatially-resolved transcriptomics is a powerful technique for understanding the organization of gene expression within tissues, providing new insights into function or disease and was named the Nature Methods of the year in 2020. In this workshop, we will demonstrate how to apply our Bioconductor package, spatialLIBD, to analyze spatially-resolved transcriptomics data (from Visium by 10x Genomics) and add spatial context to single cell RNA-seq or clinical gene datasets. We will work with the SpatialExperiment data structure and showcase gene expression visualization using spot plots. We will also cover spatial registration to identify differentially expressed genes between different regions of tissue. These results are used to inform association with previous spatial annotations and cell type populations. These analyses can be applied to different Visium and/or sc/snRNA-seq datasets using spatialLIBD functions. Finally, we will show how to test for gene set enrichment in spatial domains using an external clinical gene dataset. We will use Visium, Visium Spatial Proteogenomics (Visium-SPG), and snRNA-seq data from our recent pre-print on postmortem human brain data for these examples (doi: 10.1101/2023.02.15.528722). spatialLIBD not only provides access to data, but also has multiple utility functions for interacting and analyzing Visium data.

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