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.
Person

Principal investigator

Melanie McCoy melanie.mccoy@uwa.edu.au
Magnifying glass

Area of science

Biomedical
CPU

Systems used

Nimbus Cloud
Computer

Applications used

Flow cytometry data analysis
Partner Institution: The University of Western Australia| Project Code:

The 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)