Bioinformatics strategies for optimal interpretation of spatial-omics data in cancer

• Graduate Research Masters
• Masters by Coursework
• PhD

Spatial-omics technologies have surged in popularity over recent years. By adding spatial and morphological layers of information, spatial-omics data offers deeper insights into cell type composition and tissue formation. However, this technology is still relatively new, and no gold standard exists for data analysis. Additionally, effectively incorporating spatial information into bioinformatics analysis remains a challenge.

At the WEHI Cancer Biology and Stem Cells Division, we are leveraging various spatial-omics platforms, such as Visium, Xenium, and MERSCOPE, to study a wide range of cancer diseases. This research project focuses on developing bioinformatics methodologies, analysis pipelines, and software tools to fully unlock the potential of spatial technologies in cancer research. Moreover, we will apply our bioinformatics strategies to collaborative cancer research projects that employ spatial-omics technology.

This project is eligible for the WEHI Artificial Intelligence (AI) & Machine Learning (ML) PhD Scholarship, and is open to both domestic and international students.

The Chen lab focuses on gene expression, gene regulation, single-cell and spatial-omics, particularly in the context of cancer research. We have a strong background in RNA-seq differential gene expression, pathways analysis, differential DNA methylation analysis, and comprehensive single-cell and spatial transcriptomics integration.

Our research is divided into two main areas: scientific collaborations and methodology development. We collaborate closely with researchers within our institute and externally, conducting bioinformatics analyses on experimental data. We have a long-standing collaboration with the Breast Cancer lab at WEHI, resulting in significant discoveries and publications in high-impact journals. Additionally, we develop new statistical strategies for data generated by advanced technologies and implement these methods in software tools.