ArticleFrontiers in immunology2021
How to Prepare Spectral Flow Cytometry Datasets for High Dimensional Data Analysis: A Practical Workflow.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Gut archaea drive human MAIT cell responses.bioRxiv : the preprint server for biology · 2026Article
- Article
- VoxelCoder: Classification of human cellular phenotypes via autoencoder batch alignment and hyperdimensional representation of cytometry data.Patterns (New York, N.Y.) · 2026Article
- Navigating the Landscape of Cytometry-Based Single-Cell Proteomics: Quantification, Annotation, and Resources.International journal of molecular sciences · 2026Review
- Nuclear Histone 3 Post-Translational Modification Profiling in Whole Cells using Spectral Flow Cytometry.bioRxiv : the preprint server for biology · 2026Article
- A context-aware interpretive framework for lymphocyte immunophenotyping by flow cytometry.Frontiers in immunology · 2026Article
- Comprehensive immune profiling of human peripheral blood mononuclear cells using two complementary spectral flow cytometry panels encompassing 60 unique markers.Frontiers in immunology · 2026Article
- Development and computational analysis of high dimensional spectral flow cytometry data for the resolution of innate lymphoid cells in the mammary tumor microenvironment.Frontiers in immunology · 2026Article
- Double negative T cells (CD4Frontiers in immunology · 2026Article
- Immune monitoring for relapse of acute myeloid leukemia after allogeneic stem cell transplantation in clinical laboratories.Frontiers in immunology · 2026Review
- Dysregulation of homeostatic cytokine receptors drives prolonged T cell activation following acute SARS-CoV-2 infection in humans.Nature communications · 2025Article
- Blood and tissue correlates of steroid non-response in checkpoint inhibition-induced immune-related adverse events.Communications medicine · 2025Article
- β-adrenergic signaling blockade attenuates metastasis through activation of cytotoxic CD4 T cells.Nature communications · 2025Article
- Single-cell proteomics characterization of bone marrow hematopoiesis with distinct Ras pathway lesions.Blood advances · 2025Article
- Beyond the Limits: How Is Spectral Flow Cytometry Reshaping the Clinical Landscape and What Is Coming Next?Cells · 2025Review
- Dissecting immunophenotypic diversity in multiple myeloma via mass cytometry: a call for harmonized gating strategies.Frontiers in immunology · 2025Review
- Cord blood innate-like T cell responses in neonates born to healthy women and women living with HIV.Frontiers in immunology · 2025Article
- Identification of single-cell blasts in pediatric acute myeloid leukemia using an autoencoder.Life science alliance · 2024Article
- NKG2C and NKG2A coexpression defines a highly functional antiviral NK population in spontaneous HIV control.JCI insight · 2024Article
- Closing Editorial: Immunophenotyping in Autoimmune Diseases and Cancer 3.0.International journal of molecular sciences · 2024Article
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spectral flow cytometry is an upcoming technique that allows for extensive multicolor panels, enabling simultaneous investigation of a large number of cellular parameters in a single experiment. To fully explore the resulting high-dimensional single cell datasets, high-dimensional analysis is needed, as opposed to the common practice of manual gating in conventional flow cytometry. However, preparing spectral flow cytometry data for high-dimensional analysis can be challenging, because of several technical aspects. In this article, we will give insight into the pitfalls of handling spectral flow cytometry datasets. Moreover, we will describe a workflow to properly prepare spectral flow cytometry data for high dimensional analysis and tools for integrating new data at later time points. Using healthy control data as example, we will go through the concepts of quality control, data cleaning, transformation, correcting for batch effects, subsampling, clustering and data integration. This methods article provides an R-based pipeline based on previously published packages, that are readily available to use. Application of our workflow will aid spectral flow cytometry users to obtain valid and reproducible results.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.