Collaborating Groups
Spatial transcriptomics group:
Spatial transcriptomics (ST) is a recently developed technology that has grown in popularity, contributing to a boom in spatial biology as a discipline.
At Daub lab we are analysing what is, to our knowledge, the current largest ER+ Breast Cancer (BC) ST dataset. Within this dataset we have data for four BC subtypes: ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC, invasive lobular carcinoma (ILC, and a mixture of IDC and ILC. Uniquely, for each patient tumour sample we also have control ST slides from sites physically separated from the tumour areas. This allows us to explore a variety of questions including but not limited to: spatial patterns of gene expression in tumour bodies; heterogeneity of cell types in BC tumours; involvement of immune cells in BC tumours; differences in spatial patterns and expression levels in invasive BC subtypes (IDC and ILC) compared to less aggressive DCIS; analysis of best practices for the analysis of ST data; multimodal analysis with integration of ST data and other data types; use of machine/deep learning models to predict cancer presence from high resolution slide images alone.
There is a diverse international network of students at all levels of research from undergraduate to post doctoral level who are working on different facets of this dataset. All who are working together towards a unified objective of understanding more about this disease which is the leading cause of death for women in many countries around the world.
Dog Genome Annotation (DoGA) Project:
We have initiated a collaborative project (2017-) to generate a functional annotation of the dog genome to improve the canine models for human health.
The project will generate the most comprehensive functional information source of the dog genome to facilitate the highest resolution disease gene mappings not possible with the current reference data. This new genomic resource will become publicly available and serve the international research community to better understand the molecular backgrounds of disease, morphology and behaviour for more efficient treatment scenarios. Our project will utilize the new genome annotation to identify risk variants for common brain disorders such as epilepsy, anxiety and neurodegeneration and to understand variable expression patterns in different parts of the dogs’ and wolves’ brains.