TrackSOM: Mapping immune response dynamics through clustering of time-course cytometry data
Givanna H Putri1,2, Jonathan Chung3,4, Davis N Edwards3,5
1School of Computer Science, The University of Sydney, Sydney, New South Wales, Australia.
Insights
TrackSOM is a new method to track immune cell changes during disease. It helps understand immune responses, like in West Nile Virus infection, revealing cell dynamics linked to disease severity.
Area of Science:
- Immunology
- Computational Biology
- Bioinformatics
Background:
- Understanding immune cell dynamics is crucial for studying disease pathogenesis and developing interventions.
- Cytometry datasets provide valuable information on immune cell populations but analyzing their temporal changes is challenging.
Purpose of the Study:
- To introduce TrackSOM, a novel computational method for delineating and tracking immune cell population dynamics in cytometry data over time or disease course.
- To demonstrate the utility of TrackSOM in analyzing the immune response to West Nile Virus infection in a mouse model.
Main Methods:
- TrackSOM, a user-friendly computational tool with minimal parameters, was developed for analyzing cytometry data.
- The method was applied to mouse models of West Nile Virus infection to map immune cell kinetics.
Main Results:
- TrackSOM successfully delineated heterogeneous immune cell subpopulations and tracked their functional evolution during West Nile Virus infection.
- The method revealed correlations between immune cell dynamics and disease severity.
Conclusions:
- TrackSOM provides an integrative and dynamic overview of immune system kinetics during disease progression and resolution.
- This method facilitates the elucidation of immunopathogenesis and aids in the development of targeted immunotherapies.
Abstract:
Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, a novel method for delineating cellular populations and tracking their development over a time- or disease-course cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous subpopulations of immune cells and relating their functional evolution to disease severity. TrackSOM is easy to use, encompasses few parameters, is quick to execute, and enables an integrative and dynamic overview of the immune system kinetics that underlie disease progression and/or resolution.
