My broad research interests are to use sequencing data to understand carcinogenesis and to stratify cancers and other diseases in biologically relevant ways to derive more personalised treatments.
My current focus is bladder cancer, a relatively understudied group of diseases despite approximately 10,000 diagnoses in the UK every year. I utilise publicly available datasets such as The Cancer Genome Atlas (TCGA), apply knowledge from sequencing data of healthy human bladder generated in the Jack Birch Unit, and I am one of the bioinformatic leads analysing the bladder cancer samples of the 100,000 Genomes Project. I am interested in integrating multiple “omics” technologies into a single classification approach, the markers of carcinogenesis, and understanding the parallels between bladder cancer and other carcinoma, such as breast cancer. I am also working to apply the successes of the cancer field to chronic, benign urological conditions which lack clear molecular characterisation or diagnosis.
Beyond this focus on the bladder, I am interested in non-coding variation in the genome, particularly LTR retrotransposons and endogenous retroviruses (ERVs). My research in this area to date has been on endogenous Avian Leukosis Viruses in chicken genomes, particularly the impact of these sites on productivity and spontaneous tumour development. I aim to translate this work to human cancers of retroviral origin.
I am a Research Fellow and proleptic Lecturer in Cancer Informatics funded by York Against Cancer in honour of the charity’s 30th Anniversary.
My tutorials introduce sequencing technologies, including whole genome sequencing, RNA sequencing and the application of new long read technologies. The sessions cover where these data come from, how to correctly design experiments using sequencing, and how to visualise and interpret results. There are multiple opportunities for each student to present, as well as designing experiments and working on real sequencing data. Sequencing technologies change rapidly and we discuss new techniques and their application.
I offer computational projects in cancer genomics and transcriptomics, working with data generated at York as well as large public cohorts such as The Cancer Genome Atlas (TCGA) and the Genomics England 100,000 Genomes Project. Students will work with me directly for the duration of their project and learn highly translational data analysis skills for working with “big data”.