Protocol for large scale whole blood immune monitoring by mass cytometry and Cyto Quality Pipeline.


Journal

STAR protocols
ISSN: 2666-1667
Titre abrégé: STAR Protoc
Pays: United States
ID NLM: 101769501

Informations de publication

Date de publication:
16 12 2022
Historique:
entrez: 10 11 2022
pubmed: 11 11 2022
medline: 15 11 2022
Statut: epublish

Résumé

Mass cytometry (MC) is a powerful large-scale immune monitoring technology. To maximize MC data quality, we present a protocol for whole blood analysis together with an R package, Cyto Quality Pipeline (CytoQP), which minimizes the experimental artifacts and batch effects to ensure data reproducibility. We describe the steps to stimulate, fix, and freeze blood samples before acquisition to make them suitable for retrospective studies. We then detail the use of barcoding and reference samples to facilitate multicenter and multi-batch experiments. For complete details on the use and execution of this protocol, please refer to Rybakowska et al. (2021a) and (2021b).

Identifiants

pubmed: 36353363
doi: 10.1016/j.xpro.2022.101697
pii: S2666-1667(22)00577-9
pmc: PMC9637821
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

101697

Informations de copyright

© 2022 The Author(s).

Déclaration de conflit d'intérêts

The authors declare no competing interests.

Références

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Auteurs

Paulina Rybakowska (P)

GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain. Electronic address: paulina.rybakowska@genyo.es.

Sofie Van Gassen (S)

Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, 9000 Gent, Belgium; Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, 9000 Gent, Belgium.

Jordi Martorell Marugán (J)

GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain; Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain; Data Science for Health Research Unit, Fondazione Bruno Kessler, 38123 Trento, Italy.

Katrien Quintelier (K)

Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, 9000 Gent, Belgium; Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, 9000 Gent, Belgium; Department of Pulmonary Diseases, Erasmus MC, 3015 Rotterdam, the Netherlands.

Yvan Saeys (Y)

Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, 9000 Gent, Belgium; Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, 9000 Gent, Belgium.

Marta E Alarcón-Riquelme (ME)

GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain; Institute for Environmental Medicine, Karolinska Institute, 17177 Stockholm, Sweden.

Concepción Marañón (C)

GENYO, Centre for Genomics and Oncological Research Pfizer/University of Granada/ Andalusian Regional Government, PTS, 18016 Granada, Spain. Electronic address: concepcion.maranon@genyo.es.

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Classifications MeSH