ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.

Autor:	Sun J; Centre for Inflammation Biology and Cancer Immunology & Peter Gorer Department of Immunobiology, King's College London, London, United Kingdom., Choy D; School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom., Sompairac N; School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom., Jamshidi S; School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom., Mishto M; Centre for Inflammation Biology and Cancer Immunology & Peter Gorer Department of Immunobiology, King's College London, London, United Kingdom.; Research Group of Molecular Immunology, Francis Crick Institute, London, United Kingdom., Kordasti S; School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom.; Haematology Department, Guy's Hospital, London, United Kingdom.; Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy.
Jazyk:	angličtina
Zdroj:	ELife [Elife] 2024 Sep 06; Vol. 13. Date of Electronic Publication: 2024 Sep 06.
DOI:	10.7554/eLife.95494
Abstrakt:	Mass cytometry is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level, advancing clinical research in immune monitoring. Nevertheless, the vast data generated by cytometry by time-of-flight (CyTOF) poses a significant analytical challenge. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel toolkit for CyTOF data analysis. This framework incorporates BinaryClust, an in-house developed semi-supervised clustering tool that automatically identifies main cell types. BinaryClust outperforms existing clustering tools in accuracy and speed, as shown in benchmarks with two datasets of approximately 4 million cells, matching the precision of manual gating by human experts. Furthermore, ImmCellTyper offers various visualisation and analytical tools, spanning from quality control to differential analysis, tailored to users' specific needs for a comprehensive CyTOF data analysis solution. The workflow includes five key steps: (1) batch effect evaluation and correction, (2) data quality control and pre-processing, (3) main cell lineage characterisation and quantification, (4) in-depth investigation of specific cell types; and (5) differential analysis of cell abundance and functional marker expression across study groups. Overall, ImmCellTyper combines expert biological knowledge in a semi-supervised approach to accurately deconvolute well-defined main cell lineages, while maintaining the potential of unsupervised methods to discover novel cell subsets, thus facilitating high-dimensional immune profiling. Competing Interests: JS, DC, NS, SJ, MM, SK No competing interests declared (© 2024, Sun, Choy et al.)
Databáze:	MEDLINE
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