Chemo-radiotherapy
The 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 and analysed these using multi-parameter flow cytometry to determine whether subtypes of immune cells present in peripheral blood are associated with treatment response.
Area of science
Biomedical
Systems used
Nimbus Cloud
Applications used
Flow cytometry data analysisThe Challenge
Traditional flow cytometry data analysis methods using manual gating are very time consuming and require a priori knowledge of the cell populations of interest.
The Solution
Unsupervised hierarchical clustering analysis algorithms can be used to analyse large flow cytometry data sets, enabling faster and more objective analysis.
The Outcome
Such clustering algorithms require a large amount of memory and processing power. It would not be possible to perform these analyses for this project without use of the Nimbus service.
The Outcome
Such clustering algorithms require a large amount of memory and processing power. It would not be possible to perform these analyses for this project without use of the Nimbus service.
Cloud allocation: n3.16c64r instance (previously m2.jumbo)
