Statistical analysis of single-cell multi-omics data

Statistical analysis of single-cell multi-omics data

Project details

Single-cell transcriptomics has become the gold standard method for exploring cellular heterogeneity and cell type composition within tissues/organisms. Now with the multi-omics technologies, we can further measure multiple types of molecules from the same individual cell, allowing us to study the correlation between gene expression, DNA methylation and chromatin accessibility at the single-cell level. This will provide us a deeper understanding of some key biological processes and underlying mechanisms.

As these technologies are still relatively new to the broad scientific community, there is a huge demand for new bioinformatics strategies, adequate statistical methods and software tools for analysing these data. This project will develop novel methodologies and software tools for 1) analysing different single-cell omics data and 2) integrating multiple modalities for better interpretation of the data. 

About our research group

The Chen lab's research focuses on gene or transcript expression, alternative splicing, DNA methylation, single-cell omics and spatial technologies. We develop statistical bioinformatics methodologies and software tools to make sense of different types of sequencing data and to answer biological questions of interest.

We are a small but enthusiastic and motivated bioinformatics team, embedded in a top-class research division in cancer biology and stem cells. Through daily collaboration, you will be working at the forefront of cancer research with world-leading experts in the fields. You will have access to very exciting biological data generated by the latest cutting-edge sequencing technologies and develop novel methods to make groundbreaking discoveries in cancer research.


Email supervisors



Dr Yunshun Chen

Dr Yunshun Chen
Laboratory Head

Project Type: