ArticleNAR genomics and bioinformatics2020
Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets.
Article in NAR genomics and bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Key Considerations on CITE-Seq for Single-Cell Multiomics.Proteomics · 2025Review
- Spatial mapping of innate lymphoid cells in human lymphoid tissues and lymphoma at single-cell resolution.Nature communications · 2025Article
- CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny.BMC bioinformatics · 2024Article
- Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics.BMC bioinformatics · 2023Article
- Enhanced annotation of CD45RA to distinguish T cell subsets in single-cell RNA-seq via machine learning.Bioinformatics advances · 2023Article
- Single-Cell RNAseq Profiling of Human γδ T Lymphocytes in Virus-Related Cancers and COVID-19 Disease.Viruses · 2021Article
- Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data.Briefings in bioinformatics · 2021Article
- PD-1 blockade restores helper activity of tumor-infiltrating, exhausted PD-1hiCD39+ CD4 T cells.JCI insight · 2021Article
- Phased differentiation of γδ T and T CD8 tumor-infiltrating lymphocytes revealed by single-cell transcriptomics of human cancers.Oncoimmunology · 2021Article
- Lymphoma Heterogeneity Unraveled by Single-Cell Transcriptomics.Frontiers in immunology · 2021Review
- Longitudinal CITE-Seq profiling of chronic lymphocytic leukemia during ibrutinib treatment: evolution of leukemic and immune cells at relapse.Biomarker research · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of single-cell transcriptomic technologies yields large datasets comprising multimodal informations, such as transcriptomes and immunophenotypes. Despite the current explosion of methods for pre-processing and integrating multimodal single-cell data, there is currently no user-friendly software to display easily and simultaneously both immunophenotype and transcriptome-based UMAP/t-SNE plots from the pre-processed data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of pre-processed multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and epitopes of functional maturation in human peripheral T lymphocytes. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.
Identifiers
What OpenQuestion holds
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.