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TrackSOM: Mapping immune response dynamics through clustering of time-course cytometry data.

Givanna H PutriJonathan ChungDavis N EdwardsFelix Marsh-WakefieldIrena KoprinskaSuat DervishNicholas Jonathan Cole KingThomas Myles AshhurstMark Norman Read
Published in: Cytometry. Part A : the journal of the International Society for Analytical Cytology (2022)
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.
Keyphrases
  • single cell
  • immune response
  • high resolution
  • rna seq
  • high density
  • physical activity
  • type diabetes
  • big data
  • high fat diet induced
  • insulin resistance
  • network analysis