ReviewComputational and structural biotechnology journal2020
Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry.
Review in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Navigating the Landscape of Cytometry-Based Single-Cell Proteomics: Quantification, Annotation, and Resources.International journal of molecular sciences · 2026Review
- Prognostic impact of sarcopenia and blood biomarkers in advanced non-small cell lung cancer on first-line immune checkpoint inhibitors.Scientific reports · 2026Article
- Monitoring Immune Responses to Vaccination: A Focus on Single-Cell Analysis and Associated Challenges.Vaccines · 2025Review
- Unveiling the power of high-dimensional cytometry data with cyCONDOR.Nature communications · 2024Article
- Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Computational Methods for Single-Cell Proteomics.Annual review of biomedical data science · 2023Review
- ANPELA: Significantly Enhanced Quantification Tool for Cytometry-Based Single-Cell Proteomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Protocol for large scale whole blood immune monitoring by mass cytometry and Cyto Quality Pipeline.STAR protocols · 2022Article
- Challenges in translational machine learning.Human genetics · 2022Review
- CyTOF mass cytometry analysis of human memory CD4STAR protocols · 2022Article
- cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies.Nature communications · 2022Article
- CytofIn enables integrated analysis of public mass cytometry datasets using generalized anchors.Nature communications · 2022Article
- Assessment of Tumor Heterogeneity in High-Grade Serous Ovarian Cancer: Mass Cytometry to Understand the Complex Tumor Biology.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Breaking the Immune Complexity of the Tumor Microenvironment Using Single-Cell Technologies.Frontiers in genetics · 2022Review
- Mass cytometry profiling of human dendritic cells in blood and tissues.Nature protocols · 2021Review
- Mass-tag barcoding for multiplexed analysis of human synaptosomes and other anuclear events.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2021Article
- Making the most of high-dimensional cytometry data.Immunology and cell biology · 2021Review
- Analyzing high-dimensional cytometry data using FlowSOM.Nature protocols · 2021Review
- Data processing workflow for large-scale immune monitoring studies by mass cytometry.Computational and structural biotechnology journal · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-dimensional, single-cell cell technologies revolutionized the way to study biological systems, and polychromatic flow cytometry (FC) and mass cytometry (MC) are two of the drivers of this revolution. As up to 30-50 dimensions respectively can be measured per single-cell, they allow deep phenotyping combined with cellular functions studies, like cytokine production or protein phosphorylation. In parallel, the bioinformatics field develops algorithms that are able to process incoming data and extract the most useful and meaningful biological information. However, the success of automated analysis tools depends on the generation of high-quality data. In this review we present the most recent FC and MC computational approaches that are used to prepare, process and interpret high-content cytometry data. We also underscore proper experimental design as a key step for obtaining good quality data.
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Registered trials
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 OpenQuestion graph.