Reference health
Analyzing high-dimensional cytometry data using FlowSOM
80/80 checkable references clean · checked 2026-07-25
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
5 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 80 checked references that resolve
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ShinySOM: graphical SOM-based analysis of single-cell cytometry data
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An R‐Derived FlowSOM Process to Analyze Unsupervised Clustering of Normal and Malignant Human Bone Marrow Classical Flow Cytometry Data
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FlowRepository: A resource of annotated flow cytometry datasets associated with peer‐reviewed publications
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AutoSpill: A method for calculating spillover coefficients to compensate or unmix high-parameter flow cytometry data
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OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis
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flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification
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Immunogenomic identification and characterization of granulocytic myeloid-derived suppressor cells in multiple myeloma
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Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer
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Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma
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Immune phenotyping of diverse syngeneic murine brain tumors identifies immunologically distinct types
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Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer
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Characterization of the Impact of Daclizumab Beta on Circulating Natural Killer Cells by Mass Cytometry
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Photodepletion with 2-Se-Cl prevents lethal graft-versus-host disease while preserving antitumor immunity
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Conventional Treatment of Glioblastoma Reveals Persistent CD44+ Subpopulations
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TGF-β and IL-15 Synergize through MAPK Pathways to Drive the Conversion of Human NK Cells to an Innate Lymphoid Cell 1–like Phenotype
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Single-cell mass cytometry reveals cross-talk between inflammation-dampening and inflammation-amplifying cells in osteoarthritic cartilage
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Single-cell mass cytometry on peripheral blood identifies immune cell subsets associated with primary biliary cholangitis
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Costimulation Blockade Disrupts CD4+ T Cell Memory Pathways and Uncouples Their Link to Decline in β-Cell Function in Type 1 Diabetes
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Löfgren's syndrome sarcoidosis and Non-LS sarcoidosis prediction using 1d-Convolutional neural networks
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Single-Cell Analyses of Colon and Blood Reveal Distinct Immune Cell Signatures of Ulcerative Colitis and Crohn’s Disease
resolves10.3389/fphar.2019.01695
Ex Vivo Human Adipose Tissue Derived Mesenchymal Stromal Cells (ASC) Are a Heterogeneous Population That Demonstrate Rapid Culture-Induced Changes
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Pediatric Burn Survivors Have Long-Term Immune Dysfunction With Diminished Vaccine Response
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T-bet+ Memory B Cells Link to Local Cross-Reactive IgG upon Human Rhinovirus Infection
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Marked T cell activation, senescence, exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia
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HIV efficiently infects T cells from the endometrium and remodels them to promote systemic viral spread
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Combination rhIL-15 and Anti-PD-L1 (Avelumab) Enhances HIVGag-Specific CD8 T-Cell Function
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Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications
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flowAI: automatic and interactive anomaly discerning tools for flow cytometry data
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flow<scp>C</scp>lean: Automated identification and removal of fluorescence anomalies in flow cytometry data
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Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry
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VoPo leverages cellular heterogeneity for predictive modeling of single-cell data
The 5 references without a DOI — listed, not checked
no DOI — not checkedvan der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).
no DOI — not checkedKotecha, N., Krutzik, P. O. & Irish, J. M. Web-based analysis and publication of flow cytometry experiments. Curr. Protoc. Cytom. 53, 10.17.1–10.17.24 (2010).
no DOI — not checkedFlowJoTM Software (Becton, Dickinson, 2019).
no DOI — not checkedFinak, G. & Jiang, M. flowWorkspace: infrastructure for representing and interacting with gated and ungated cytometry data sets (2020).
no DOI — not checkedMersmann, O., Beleites, C., Hurling, R., Friedman, A. & Ulrich, J. M. microbenchmark: Accurate Timing Functions. https://rdrr.io/cran/microbenchmark/
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