TrackSOM-evaluations

This repository contains scripts to reproduce the evaluations, tables, and figures in:

1. Our paper which introduces the TrackSOM algorithm.
2. The COVID-19 paper which uses TrackSOM to profile acute and convalescence COVID-19 samples.

TrackSOM is a clustering and temporal cluster tracking algorithm for clustering and tracking cellular populationchanges in time- and disease-course cytometry data.

Please cite the following preprint if you find TrackSOM useful in your research.

@article {Putri2021.06.08.447468,
	author = {Putri, Givanna Haryono and Chung, Jonathan and Edwards, Davis N and Marsh-Wakefield, Felix and Dervish, Suat and Koprinska, Irena and King, Nicholas JC and Ashhurst, Thomas Myles and Read, Mark Norman},
	title = {TrackSOM: mapping immune response dynamics through sequential clustering of time- and disease-course single-cell cytometry data},
	elocation-id = {2021.06.08.447468},
	year = {2021},
	doi = {10.1101/2021.06.08.447468},
	publisher = {Cold Spring Harbor Laboratory},
	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, 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.Competing Interest StatementThe authors have declared no competing interest.},
	URL = {https://www.biorxiv.org/content/early/2021/06/09/2021.06.08.447468},
	eprint = {https://www.biorxiv.org/content/early/2021/06/09/2021.06.08.447468.full.pdf},
	journal = {bioRxiv}
}

The preprint titled TrackSOM: mapping immune response dynamics through sequential clustering of time- and disease-course single-cell cytometry data can be found on bioRxiv.

TrackSOM paper

The scripts are stored in tracksom_paper directory and organised according to the datasets: synthetic_dataset, wnv_bm_dataset, and wnv_cns_dataset.

The raw dataset can be downloaded from the Open Science Framework portal: https://osf.io/8dvzu/

COVID-19 paper

TrackSOM was used to analyse COVID-19 temporal data published in Cell Reports Medicine journal:

Koutsakos, M., Rowntree, L.C., Hensen, L., Chua, B.Y., van de Sandt, C.E., Habel, J.R., Zhang, W., Jia, X., Kedzierski, L., Ashhurst, T.M. and Putri, G.H., 2021. Integrated immune dynamics define correlates of COVID-19 severity and antibody responses. Cell Reports Medicine, p.100208.

R scripts to reproduce evaluations and figures in the paper are available in the covid19_paper directory.