This module will introduce the analysis of single cell & spatial transcriptomics data to reveal cell and tissue specific patterns not detectable in traditional RNA sequencing data. We will get familiarity with single cell and spatial data types and their features. We will use python and R packages for hands-on analyses of single cell data, focusing on data pre-processing, normalisation, dimensionality reduction, clustering, identifying cell type markers. We will use Python to introduce machine learning concepts, common approaches, and hands-on implementation of deep learning models applied to spatial transcriptomics data.

Primary Instructor:
A/P Quan Nguyen
A/P Quan Nguyen is a Group Leader at the Institute for Molecular Bioscience (IMB), The University of Queensland. He is leading the Genomics and Machine Learning lab to study cancer-immune cells at single-cell resolution and within their spatial tissue context. His research interest is about revealing gene and cell regulators that determine the tissue states of a complex cancer. Particularly, he is interested in quantifying spatial patterns of cell organisation and the screening of cell-cell interactions in undissociated tissue samples to find new gene and cell targets that can be used to improve cancer diagnosis, prognosis, and treatments.

Co-instructors:
Dr Xiao Tan
Dr Xiao Tan is a postdoctoral researcher in the Genomics and Machine Learning lab (GML), Institute for Molecular Bioscience (IMB), The University of Queensland (UQ). His research interest is about modelling the molecular and morphological changing for cells in the tissue context. Particularly, his research focuses on deep learning based integration of multi-modal tissue imaging and sequencing data for predicting cell states and molecular profile in cancer.

Mr Onkar Mulay
Mr. Onkar Mulay is the Ph.D. student in the Genomics and Machine Learning lab, Institute for Molecular Bioscience (IMB), The University of Queensland. He graduated from UQ with a master degree in engineering, followed by a year of work as a bioinformatician prior to his PhD. His research focuses on the machine learning analyses of spatial and single-cell omics data.

<< Go back to Main Page