Author: Putri, Givanna H.; Chung, Jonathan; Edwards, Davis N.; Marsh-Wakefield, Felix; Dervish, Suat; Koprinska, Irena; King, Nicholas J.C.; Ashhurst, Thomas M.; Read, Mark N.
Title: TrackSOM: mapping immune response dynamics through sequential clustering of time- and disease-course single-cell cytometry data Cord-id: ywb8lc0l Document date: 2021_6_9
ID: ywb8lc0l
Snippet: Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, an algorithm which delineates cellular populations and tracks their development over a time- or disease-course of cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous sub-populations of immune cells and relating their function
Document: Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, an algorithm which delineates cellular populations and tracks their development over a time- or disease-course of cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous sub-populations 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.
Search related documents:
Co phrase search for related documents, hyperlinks ordered by date