Cytometry has rapidly become one of the routinely used techniques in clinical and research settings to classify, characterise, and quantify cells. Recent technological advancements in flow cytometry and mass cytometry (CyTOF) have facilitated simultaneous measurement of about 40 distinct parameters per cell. This rapid and unprecedented increase in the dimensionality of cytometry data sets poses significant challenges for conventional data analysis methods. Despite the emergence of higher dimensional R-based computational methods to tackle these complex data sets, a vast majority of cytometry data is still analysed manually in commercial software by sequentially gating populations. Accordingly, there exists an urgent need to develop robust open-source software to integrate manual and computational analysis methods under a unified framework. Here I will present CytoExploreR, an open-source R package developed at JCSMR, which integrates the best features of commercially available software with the powerful computational tools available in R. Over the past year, CytoExploreR has become a comprehensive collection of tools to interactively explore and analyse your cytometry data from beginning to end. In this introductory seminar, I will present some of the key features of CytoExploreR, including high-resolution exploratory visualisations, data transformations, manual and automated compensation of fluorescent spillover, spillover spreading matrices, manual and automated gating, and computation of population-level statistics. Starting next year, the Imaging and Cytometry Facility (ICF) at JCSMR will be the first facility in the world to adopt CytoExploreR as a standard component of its induction process. This training will uniquely position JCMSR users at the forefront of cytometry data analysis and provide users with the capacity to contribute to the development of custom-made software to meet their research needs.
About the Speaker
Dillon Hammill is a third-year PhD student at JCSMR from the Cancer and Vascular Biology Group in the ACRF Department of Cancer Biology and Therapeutics. His research aims to identify novel immunotherapies for the treatment of cancer, through delivery of specific combinations of immune danger signals into solid tumours to promote anti-tumour immune responses. During his time as a PhD student, Dillon acquired a passion for data science and developed CytoExploreR, a new open-source software package for cytometry data analysis. Recently, Dillon received a travel award to present this work at the annual Australasian Cytometry Society (ACS) meeting in Melbourne, where he won the award for best research oral presentation.