Course - SPATIAL OMICS & MULTIPLEXED IMAGE ANALYSIS
Dates: Online 6-9 November 2023
COURSE OVERVIEW
During this course we will discuss basics and introduce state-of-the-art software-tools tailored for spatial omics and multiplexed image analysis. The most common workflows can be divided in three steps: (i) processing/preparing the images for cellular segmentation, (ii) extraction of the individual marker intensities for each cell which are subsequently used for cell phenotyping and (iii) neighborhood analysis to quantify interactions between the different cell types in the tissue. In this course we will visit each of these steps and present algorithms and software-tools used for processing, analysis and visualization of images and data. These tools include among others MCMICRO, SCIMAP, QuPath, Fiji and napari. The course will be delivered in 4 days (see program below). Each day we will have a presentations as well as hands-on sessions.
INTENDED AUDIENCE
The course is intended for biologists and computational biologists who work with multiplexed images at a protein level (antibodies/immunofluorescence). Basic experience in programming with python, running programs through command line and fluorescence microscopy come in handy for this course but they are not necessary.
LEARNING OUTCOMES
By the end of the course, participants will be able to:
- Use the MCMICRO pipeline to perform image processing on multiplexed images.
- Use QuPath, napari and Fiji to carry out annotations and visual quality control on images.
- Do cell phenotyping and basic spatial analysis with SCIMAP.
- Perform neighborhood analysis with e.g., MISTY and SpatialLDA.
- Carry out a complete spatial analysis pipeline for multiplexed data, i.e., from image processing to cell segmentation, cell phenotyping and neighborhood analysis.
SESSION CONTENT
Day 1 - 2-8 pm Berlin time - Image acquisition principles and image visualization
- Introduction to spatial omics and multiplexed imaging (Denis Schapiro)
- Fluorescence microscopy principles
- Spatial multi-omics technologies (proteins/antibodies vs transcriptomics)
- Multiplex Immunofluorescence microscopy
- Hands-on session
- Image visualization software : Fiji, QuPath, napari.
- Image processing basics
Day 2 - 2-8 pm Berlin time - Image preprocessing for multiplexed imaging
- Basic quality control
- Visualization of individual processing steps
- Image processing steps
- Illumination correction
- Registration and stitching
- Background subtraction
- Segmenting Tissue Microarrays
- Hands-on session
- MCMICRO pipeline
Day 3 - 2-8 pm Berlin time - Image analysis workflow for multiplexed imaging
- Cell segmentation algorithms
- Cell mask and extraction of cell features
- Cell type calling and clustering methods
- Spatial analysis of cells in tissues
- Hands-on session
- SCIMAP
Day 4 - 2-8 pm Berlin time - Cell type annotation and neighborhood analysis
- Cell type calling/ Cell type free
- Manual gating
- Clustering (e.g., Phenograph)
- Deep-learning methods
- Definition of cellular neighborhoods.
- Neighborhood analysis algorithms
- Sample comparison
- Identification of significant relationships.
- Neighborhood identification.
- Short and long range interactions (Misty, NCEM)
- Hands-on session
- Misty
- SpatialLDA
