Multi-assay data

Lukas M. Weber

Leader(s)

Difficulty & duration

  • difficulty: intermediate
  • duration: 1-2 days

Abstract

Our current aims are:

  • Finalize SpatialExperiment class structure by creating and testing example datasets from several technological platforms (to be collected in STdata package)
  • Adapt visualization functions for data from each platform (to be collected in ggspavis package)
  • Create a short analysis workflow using one of the example datasets from each platform

This will allow us to build an integrated Bioconductor-based infrastructure for analyzing spatially resolved transcriptomics data. Ultimately, this will all be showcased in our OSTA online book.

So far, we have mainly worked with data from the 10x Genomics Visium platform. The STdata package (under development) currently contains two example datasets from the Visium platform (human DLPFC and mouse coronal).

In the future, we will also increasingly expect multi-omics spatial data to be generated, e.g. spatial transcriptomics and protein co-detection.

In this challenge, we aim to test whether multi-omics spatial data can be stored in SpatialExperiment objects, and/or whether additional modifications to the class are required. In particular, we can re-use the altExp functionality from SingleCellExperiment. Alternatively, it may be possible that we eventually need to develop a new class, extending MultiAssayExperiment.

Targets

This challenge consists of:

  • selecting a multi-omics spatial dataset, e.g. from the 10x Genomics Visium website
  • writing a script to format this into a SpatialExperiment object, making use of the altExp functionality from SingleCellExperiment
  • discuss whether additional functionality from MultiAssayExperiment may be required for storing this data

This challenge is relatively open-ended, and may include some group discussion on the best choice of class structure for multi-omics spatial data.