RT Journal Article
T1 Data processing workflow for large-scale immune monitoring studies by mass cytometry
A1 Rybakowska, Paulina
A1 Van Gassen, Sofie
A1 Quintelier, Katrien
A1 Saeys, Yvan
A1 Alarcón-Riquelme, Marta E.
A1 Marañón, Concepción
K1 Mass cytometry
K1 Semi-automated data preprocessing
K1 Immune phenotyping
K1 Data normalization
K1 Quality control
K1 Workflow
K1 Artifacts
K1 Flow cytometry
K1 Control de calidad
K1 Flujo de trabajo
K1 Artefactos
K1 Citometría de Flujo
K1 Monitorización inmunológica
K1 Inmunofenotipificación
AB Mass cytometry is a powerful tool for deep immune monitoring studies. To ensure maximal data quality, a careful experimental and analytical design is required. However even in well-controlled experiments variability caused by either operator or instrument can introduce artifacts that need to be corrected or removed from the data. Here we present a data processing pipeline which ensures the minimization of experimental artifacts and batch effects, while improving data quality. Data preprocessing and quality controls are carried out using an R pipeline and packages like CATALYST for bead-normalization and debarcoding, flowAI and flowCut for signal anomaly cleaning, AOF for files quality control, flowClean and flowDensity for gating, CytoNorm for batch normalization and FlowSOM and UMAP for data exploration. As proper experimental design is key in obtaining good quality events, we also include the sample processing protocol used to generate the data. Both, analysis and experimental pipelines are easy to scale-up, thus the workflow presented here is particularly suitable for large-scale, multicenter, multibatch and retrospective studies.
PB Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology
YR 2021
FD 2021-05-21
LK http://hdl.handle.net/10668/4361
UL http://hdl.handle.net/10668/4361
LA en
NO Rybakowska P, Van Gassen S, Quintelier K, Saeys Y, Alarcón-Riquelme ME, Marañón C. Data processing workflow for large-scale immune monitoring studies by mass cytometry. Comput Struct Biotechnol J. 2021 May 21;19:3160-3175
DS RISalud
RD Apr 8, 2025