CYBERTRACK2.0: zero-inflated model-based cell clustering and population tracking method for longitudinal mass cytometry data

Abstract Summary Recent advancements in high-dimensional single-cell technologies, such as mass cytometry, enable longitudinal experiments to track dynamics of cell populations and identify change points where the proportions vary significantly. However, current research is limited by the lack of to...

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Published inBioinformatics (Oxford, England) Vol. 37; no. 11; pp. 1632 - 1634
Main Authors Minoura, Kodai, Abe, Ko, Maeda, Yuka, Nishikawa, Hiroyoshi, Shimamura, Teppei
Format Journal Article
LanguageEnglish
Published Oxford University Press 12.07.2021
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Summary:Abstract Summary Recent advancements in high-dimensional single-cell technologies, such as mass cytometry, enable longitudinal experiments to track dynamics of cell populations and identify change points where the proportions vary significantly. However, current research is limited by the lack of tools specialized for analyzing longitudinal mass cytometry data. In order to infer cell population dynamics from such data, we developed a statistical framework named CYBERTRACK2.0. The framework’s analytic performance was validated against synthetic and real data, showing that its results are consistent with previous research. Availability and implementation CYBERTRACK2.0 is available at https://github.com/kodaim1115/CYBERTRACK2. Supplementary information Supplementary data are available at Bioinformatics online.
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The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.
ISSN:1367-4803
1367-4811
1367-4811
DOI:10.1093/bioinformatics/btaa873