Single-cell data integration
Trainer: Shila Ghazanfar
Overview: This keynote will summarise the recent advances in single cell transcriptomics and multiomics technologies, describe the manifold approaches for single cell data integration including state-of-the-art tools, and highlight current open problems in single cell multiomics data integration and their proposed solutions. Additionally, we will cover concepts in working with integrated single cell data such as dimensionality reduction and graph representations, computational infrastructure for handling single cell data in R and Python, and describe approaches for static, dynamic and interactive visualisation of single cell multiomics data. Questions and discussion points are encouraged!
Learning outcomes
By the end of this keynote you will be able to:
- Describe concepts and issues surrounding single cell multiomics data integration
- Identify computational tools for handling and analysing such data
- Explore common issues and specific approaches for visualising single cell multiomics data
Materials: