Chemo-radiotherapyThe overall project aim is to identify predictors of response to chemo-radiotherapy in patients with colorectal cancer. We have collected blood samples pre- and post- treatment from >100 patients with colorectal cancer and analysed these using multi-parameter flow cytometry to determine whether subtypes of immune cells present in peripheral blood are associated with treatment response.
Principal investigatorMelanie McCoy firstname.lastname@example.org
Area of scienceBiomedical
Applications usedUnsupervised hierarchical clustering algorithms through R including Citrus, Phenograph and UMAP
Partner Institution: The University of Western Australia | Project Code: Chemo-radiotherapy
Traditional methods of flow cytometry data analysis are time consuming and require a priori knowledge of cell populations of interest.
Unsupervised hierarchical clustering algorithms enable faster and more objective analysis of large flow cytometry data sets.
Such clustering algorithms require large amounts of memory & processing power. It would not be possible to perform these analyses for this project without use of the Nimbus service.