Introduction to Spatial omic analyses

Stefano Mangiola, South Australian immunoGENomics Cancer Institute1, Walter and Eliza Hall Institute2

Source: vignettes/Introduction.Rmd

Instructors

Dr. Stefano Mangiola is leading the Computational Cancer immunology group at the South Australian immunoGENomics Cancer Institute (SAiGENCI). He uses single-cell and spatial technologies to investigate the tumor microenvironment and the immune system. Beyong data production, his focus in on the integration and modelling of large-scale single-cell data resources. He is the author of tidytranscriptiomics and co-leads the tidyomics endevour.

Malvica Kharbanda expert of spatial analyses at the .

Workshop partner: Physalia

Workshop goals and objectives

What you will learn

  • The basics of spatial profiling technologies
  • Analysis and manipulation of sequencing-based spatial data.
  • The basics of tidy R analyses of biological data with tidyomics
  • How to interface SpatialExperiment with tidy R manipulation and visualisation
  • Analysis and manipulation of imaging-based spatial data.

Getting started

Local

You can view the material at the workshop webpage

here.

Useful complementary resource: the Bioconductor book Orchestrating Spatial Transcriptomics Analysis with Bioconductor (OSTA).

Workshop package installation

If you want to install the packages and material post-workshop, the instructions are below. The workshop is designed for R 4.4 and Bioconductor 3.19.

# Install workshop package
#install.packages('BiocManager')
BiocManager::install("tidyomics/tidySpatialWorkshop", dependencies = TRUE)
    
# Then build the vignettes
BiocManager::install("tidyomics/tidySpatialWorkshop", build_vignettes = TRUE, force=TRUE)

# To view vignette
library(tidySpatialWorkshop)
vignette("Introduction")

Interactive execution of the vignettes

From command line, and enter the tidySpatialWorkshop directory.

# Open the command line
git clone git@github.com:tidyomics/tidySpatialWorkshop.git

Alternatively download the git zipped package. Uncompress it. And enter the directory.

Announcements

Tidyomics is now published in (Nature Methods)[https://www.nature.com/articles/s41592-024-02299-2]. And available here[https://www.biorxiv.org/content/10.1101/2023.09.10.557072v3].

Introduction to Spatial Omics

Objective

Provide a foundational understanding of spatial omics, covering different technologies and the distinctions between imaging and sequencing in experimental and analytical contexts.

Workshop Structure

Day 1
1. Welcome and Introduction
  • Introduction of the instructor
  • Introduction of the crowd
  • Overview and goals of the workshop.
2. What is Spatial Omics?
  • Definition and significance in modern biology.
  • Key applications and impact.
  • Overview of different spatial omics technologies.
  • Comparison of imaging-based vs sequencing-based approaches.
3. Sequencing Spatial Omics
  • Detailed comparison of methodologies.
  • Experimental design considerations.
  • Data analysis challenges and solutions.
5. Analysis of sequencing based spatial data
  • Getting Started with SpatialExperiment.
  • Data Visualisation and Manipulation.
  • Quality control and filtering.
  • Dimensionality reduction.
  • Spatial Clustering.
  • Deconvolution of pixel-based spatial data.
Day 2
1. Introduction to tidyomics
  • Use tidyverse on spatial, single-cell, pseudobulk and bulk genomic data
2. Working with tidySpatialExperiment
  • tidySpatialExperiment package
  • Tidyverse commands
  • Advanced filtering/gating and pseudobulk
  • Work with features
  • Summarisation/aggregation
  • tidyfying your workflow
  • Visualisation
Day 3
1. Imaging Spatial Omics
  • Detailed comparison of methodologies.
  • Experimental design considerations.
  • Data analysis challenges and solutions.
2. Spatial analyses of imaging data
  • Working with imaging-based data in Bioconductor with MoleculeExperiment
  • Aggregation and analysis
  • Clustering
  • Neighborhood analyses

  1. ↩︎

  2. <mangiola.s at wehi.edu.au>↩︎