1 Giotto Suite Workshop 2024

Workshop: Spatial multi-omics data analysis with Giotto Suite

1.1 Instructors

Ruben Dries: Assistant Professor of Medicine at Boston University
Joselyn Cristina Chávez Fuentes: Postdoctoral fellow at Icahn School of Medicine at Mount Sinai
Jiaji George Chen: Ph.D. student at Boston University
Junxiang Xu: Ph.D. student at Boston University
Edward C. Ruiz: Ph.D. student at Boston University
Jeff Sheridan: Postdoctoral fellow at Boston University
Iqra Amin: Bioinformatician at Boston University
Wen Wang: Postdoctoral fellow at Icahn School of Medicine at Mount Sinai

Day 1: Introduction
- Spatial omics technologies
  - Spatial sequencing
  - Spatial in situ
  - Spatial proteomics
  - spatial other: ATAC-seq, lipidomics, etc
- Introduction to the Giotto package
  - Ecosystem
  - Installation + python environment
  - Giotto instructions
- Data formatting and Pre-processing
- Creating a Giotto object
  - From matrix + locations
  - From subcellular raw data (transcripts or images) + polygons
  - Using convenience functions for popular technologies (Vizgen, Xenium, CosMx, …)
- Spatial plots
- Subsetting:
  - Based on IDs
  - Based on locations
  - Visualizations
- Introduction to spatial multi-modal dataset (10X Genomics breast cancer) and goal for the next days
- Quality control
  - Statistics
- Normalization
- Feature selection:
  - Highly Variable Features:
    - loess regression
    - binned
    - pearson residuals
  - Spatial variable genes
- Dimension Reduction
  - PCA
  - UMAP/t-SNE
  - Visualizations
- Clustering
  - Non-spatial
    - k-means
    - Hierarchical clustering
    - Leiden/Louvain
  - Spatial
    - Spatial variable genes
    - Spatial co-expression modules

Day 2: Spatial Data Analysis
- Spatial sequencing based technology: Visium
  - Differential expression
  - Enrichment & Deconvolution
    - PAGE/Rank
    - SpatialDWLS
    - Visualizations
  - Interactive tools
  - Spatial expression patterns
    - Spatial variable genes
    - Spatial co-expression modules
    - Spatial HMRF
- Spatial sequencing based technology: Visium HD
  - Tiling and aggregation
  - Scalability (duckdb) and projection functions
  - Spatial expression patterns
    - Spatial co-expression module
- Spatial in situ technology: Xenium
  - Read in raw data
    - Transcript coordinates
    - Polygon coordinates
    - Visualizations
  - Overlap txs & polygons
    - Typical aggregated workflow
    - Feature/molecule specific analysis
    - Visualizations
  - Transcript enrichment GSEA
  - Spatial location analysis
    - Spatial cell type co-localization analysis
    - Spatial niche analysis
    - Spatial niche trajectory analysis
    - Visualizations
- Spatial proteomics: multiplex IF
  - Read in raw data
    - Intensity data (IF or any other image)
    - Polygon coordinates
    - Visualizations
  - Overlap intensity & workflows
    - Typical aggregated workflow
    - Visualizations

Day 3: Advanced Tutorials
- Multiple samples
  - Create individual giotto objects
  - Join Giotto Objects
  - Perform Harmony and default workflows
  - Visualizations
- Spatial multi-modal
  - Co-registration of datasets
  - Examples in giotto suite manuscript
- Multi-omics integration
  - Example in giotto suite manuscript
- Interoperability w/ other frameworks
  - AnnData/SpatialData
  - SpatialExperiment
  - Seurat
- Interoperability w/ isolated tools
  - Spatial niche trajectory analysis
- Interactivity with the R/Spatial ecosystem
  - Kriging
- Contributing to Giotto

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