Spatial omics data analysis

Description

This workshop provides resources to advanced tools for analysis of spatial datasets . It is aimed towards biologists, researchers, computer scientists or data analysts planning to run, analyse and interpret single cells RNA-seq experiments independently.

Topics covered

• Hands-on experience with ST (Visium), ISS, scRNAseq data analysis
• Fluorescence-based image formats, standards and quality control
• Image alignment, registration and ISS decoding
• Nuclei-based and segmentation-free cell identification
• Data imputation using ISS and single cell datasets
• Analysis of Spatial Transcriptomics dataset
• Cell-type deconvolution (ST and single cell)
• Cell-cell and ligand-receptor interaction analysis
• Mapping of multiple spatial data to a common reference
• High-resolution projection of gene expression to H&E images
• Interactive visualisation of spatial omics data

Pre-requisites

Minimal:

• Basic knowledge in Python
• Have miniconda3 installed in your computer

Desirable:

• Previous experience with single cell RNA-seq analysis is an advantage

Level

beginner