Tutorials

Notebooks tailored to showcase specific functionalities of the SpatialData ecosystem. See the bottom of this page for links to analysis tutorials for external methods that use SpatialData as a data model.

Basic

• Intro to SpatialData

• Transformations and coordinate systems

• Spatial query/subsampling

• Annotating regions of interest with napari

• Use landmark annotations to align multiple -omics layers

Intermediate

• Create SpatialData objects from scratch

• Working with annotations in SpatialData

• Filtering SpatialData elements with Table Queries

• I. Use SpatialData with your data: the SpatialData object.

• II. Use SpatialData with your data: SpatialElements and tables

• Integrate/aggregate signals across spatial layers

• Interchangeability between raster and vector representations

• Squidpy integration

• Deep learning example on image tiles

Technology-specific

Many different technologies can be visualised out-of-the-box. See below for a couple of examples. See the example datasets for additional technologies represented in SpatialData.

• Technology focus: 10x Genomics Visium

• Technology focus: MIBI-TOF

• Technology focus: MERFISH

• Technology focus: Visium HD

• Technology focus: Visium HD (SpaceRanger 4.0)
• Download Visium HD example dataset from 10x public data repository
• Read in Visium HD data
• Visualize the images and segmentations
• Quality control and filtering
• Normalization and Clustering
• Calculate centroids

• Technology focus: Xenium

• Technology focus: SpaceM

Advanced

Advanced tutorials that showcase more complex functionalities of the SpatialData ecosystem.

• Implicit performance improvements when plotting raster data

• Raster data and translations (technical topic)
• Other technical topics

External tutorials

Links to the tutorials for (some) external analysis methods that use SpatialData as a data model.

Methods:

• Squidpy: Spatial Single Cell Analysis in Python

• SPArrOW: A library for Spatial Transcriptomics Data Analysis

• SOPA: Spatial-omics pipeline and analysis

• Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Workshop tutorials:

• A hands-on introduction into the analysis of targeted spatial transcriptomics data using the SPArrOW pipeline developed by the Yvan Saeys group (VIB)