ArticleiScience2022
Comprehensive multi-omics single-cell data integration reveals greater heterogeneity in the human immune system.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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Who cites it
12 citing papers in PubMed.
- Modeling human B cell development with pluripotent stem cells.bioRxiv : the preprint server for biology · 2026Article
- STING synergizes with TOX suppressing HO-1 expression to trigger ferroptosis in tumor-infiltrating CD8+ T cell and immunotherapy resistance.Nature communications · 2026Article
- Immune reprogramming in the bone marrow microenvironment: a new perspective on the bone immune microenvironment of postmenopausal osteoporosis.Frontiers in immunology · 2026Review
- Integration of Single-Cell RNA Sequencing Data and Bulk Sequencing Data to Characterise the CD8+ T-Cell Exhaustion Mediated Immune Microenvironment in CRC.Journal of cellular and molecular medicine · 2025Article
- Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice.Nature reviews. Immunology · 2024Review
- Theoretical framework for the difference of two negative binomial distributions and its application in comparative analysis of sequencing data.Genome research · 2024Article
- Applications of Flow Cytometry in Drug Discovery and Translational Research.International journal of molecular sciences · 2024Review
- Long COVID manifests with T cell dysregulation, inflammation and an uncoordinated adaptive immune response to SARS-CoV-2.Nature immunology · 2024Article
- Spatial Transcriptomic Technologies.Cells · 2023Review
- Long COVID manifests with T cell dysregulation, inflammation, and an uncoordinated adaptive immune response to SARS-CoV-2.bioRxiv : the preprint server for biology · 2023Article
- Transcriptional reprogramming of infiltrating neutrophils drives lung pathology in severe COVID-19 despite low viral load.Blood advances · 2023Article
- Integrated Analysis of Multiomics Data Identified Molecular Subtypes and Oxidative Stress-Related Prognostic Biomarkers in Glioblastoma Multiforme.Oxidative medicine and cellular longevity · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Single-cell transcriptomics enables the definition of diverse human immune cell types across multiple tissues and disease contexts. Further deeper biological understanding requires comprehensive integration of multiple single-cell omics (transcriptomic, proteomic, and cell-receptor repertoire). To improve the identification of diverse cell types and the accuracy of cell-type classification in multi-omics single-cell datasets, we developed SuPERR, a novel analysis workflow to increase the resolution and accuracy of clustering and allow for the discovery of previously hidden cell subsets. In addition, SuPERR accurately removes cell doublets and prevents widespread cell-type misclassification by incorporating information from cell-surface proteins and immunoglobulin transcript counts. This approach uniquely improves the identification of heterogeneous cell types and states in the human immune system, including rare subsets of antibody-secreting cells in the bone marrow.
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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.