Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Unravelling B cell heterogeneity: insights into flow cytometry-gated B cells from single-cell multi-omics data

18 Apr 2024

Abstract excerpt

Introduction B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches. Methods By analysing multi-omics single-cell data from healthy individuals and...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer Immunotherapy and Biomarkers
Share to Single-cell and spatial transcriptomics
Share to T-cell and B-cell Immunology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 38707902
DOI: 10.3389/fimmu.2024.1380386

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Unravelling B cell heterogeneity: insights into flow cytometry-gated B cells from single-cell multi-omics dataPMID 38707902Read ↗

An integrated multi-omic single cell atlas to redefine human B cell memorySemantic proximity Read ↗

A pipeline to unravel complexity in human peripheral blood B cell subsets through multiomic cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) analysesSemantic proximity Read ↗

Comprehensive multi-omics single-cell data integration reveals greater heterogeneity in the human immune systemSemantic proximity Read ↗

OMIP ‐109: 45‐color full spectrum flow cytometry panel for deep immunophenotyping of the major lineages present in human peripheral blood mononuclear cells with emphasis on the T cell memory compartmentSemantic proximity Read ↗

Unraveling B cell trajectories at single cell resolutionSemantic proximity Read ↗

Cyto-Feature Engineering: A Pipeline for Flow Cytometry Analysis to Uncover Immune Populations and Associations with Disease.Semantic proximity Read ↗

OMIP-118: A 38-Marker Spectral Flow Cytometry Panel to Assess Human Regulatory T Cell Phenotype and Lineage Plasticity.Semantic proximity Read ↗

Mass cytometry: exploring the immune landscape of systemic autoimmune and inflammatory diseases in the past fourteen yearsSemantic proximity Read ↗

ImmunoPheno: A Computational Framework for Data-Driven Design and Analysis of Immunophenotyping ExperimentsSemantic proximity Read ↗

Characterization of Human B Cell Hematological Malignancies Using Protein-Based ApproachesSemantic proximity Read ↗

Integrated single-cell (phospho-)protein and RNA detection uncovers phenotypic characteristics of human antibody secreting cellsSemantic proximity Read ↗

Single-cell omics-based characterization of human basophils reveals two transcriptionally distinct populationsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.