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.
Summary
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.
