Find the book at: https://drieslab.github.io/giotto_workshop_2024/

Find more information about Giotto Suite at www.giottosuite.com

• 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

• 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