- Webinar Speakers
Dr. Quan Nguyen
Group Leader, Institute for Molecular Bioscience (IMB)
The University of QueenslandHe is leading the Genomics Machine Learning (GML) lab to study development and disease in single cells in spatial tissue contexts. Using machine-learning and genomic approaches, his group are integrating single-cell spatiotemporal data with large-scale population genomics data to find causal relationship between DNA variants, gene expression and diseases. Currently, his GML lab are pioneering in developing machine learning methods for combining sequencing and imaging data. The lab is generating spatial transcriptomics data for different tissues and organs. In the past three years, he has contributed to the development of x8 open-source software, x2 web applications, and x4 databases for analysis of single cell data. He has published in top tier journals, including Cell, Cell Stem Cell, Nature Protocols, Nature Communications, Genome Research, Genome Biology and a prize-winning paper in GigaScience.
- Webinar Abstract
Spatial transcriptomics (ST) is emerging as the ‘next-generation’ single-cell RNA sequencing technology, as it adds an important spatial dimension to the transcriptome-wide gene expression data for cells within an intact tissue. From the same tissue section, ST generates three datatypes, including tissue-morphology, spatial location, and gene expression data. We hypothesise that integrating all three multimodal datatypes improves the accuracy and sensitivity in identifying cell types, cell-cell interactions and their interconnected transcriptional regulation within a physiologically intact tissue.
In this talk, I will introduce the generation and analysis of spatial transcriptomics data as an unbiased and systematic approach to study diseases and tissues. I will present work from my lab and collaborators in studying cellular responses to damages in the central nervous systems in mouse models with traumatic brain injury and spinal cord injury. Next, I will describe our spatial transcriptomics analysis methods to study cancer, with examples on breast cancer and skin cancer. Finally, I will discuss approaches to validate findings from spatial transcriptomics analysis.
* This webinar is conducted by Illumina in collaboration with 10x Genomics. 